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Data Analysis in R
 
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Here are two examples of numeric and non numeric data analyses. Both files are obtained from infochimps open access online database.
Views: 43692 Ani Aghababyan
Introduction to Data Science with R - Data Analysis Part 1
 
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Part 1 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 1042777 David Langer
Basic Data Analysis in RStudio
 
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This clip explains how to produce some basic descrptive statistics in R(Studio). Details on http://eclr.humanities.manchester.ac.uk/index.php/R_Analysis. You may also be interested in how to use tidyverse functionality for basic data analysis: https://youtu.be/xngavnPBDO4
Views: 143949 Ralf Becker
R Tutorial For Beginners | R Programming Tutorial l R Language For Beginners | R Training | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R Tutorial (R Tutorial Blog: https://goo.gl/mia382) will help you in understanding the fundamentals of R tool and help you build a strong foundation in R. Below are the topics covered in this tutorial: 1. Why do we need Analytics ? 2. What is Business Analytics ? 3. Why R ? 4. Variables in R 5. Data Operator 6. Data Types 7. Flow Control 8. Plotting a graph in R Check out our R Playlist: https://goo.gl/huUh7Y Subscribe to our channel to get video updates. Hit the subscribe button above. #R #Rtutorial #Ronlinetraining #Rforbeginners #Rprogramming How it Works? 1. This is a 5 Week Instructor led Online Course, 30 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you: 1. Understand concepts around Business Intelligence and Business Analytics 2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others 3. Apply various supervised machine learning techniques 4. Perform Analysis of Variance (ANOVA) 5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc 6. Use various packages in R to create fancy plots 7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights - - - - - - - - - - - - - - - - - - - Who should go for this course? This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics. - - - - - - - - - - - - - - - - Why learn Data Analytics with R? The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Telegram: https://t.me/edurekaupdates
Views: 538003 edureka!
R Studio: Importing & Analyzing Data
 
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Tutorial on importing data into R Studio and methods of analyzing data.
Views: 198660 MrClean1796
R programming for beginners – statistic with R (t-test and linear regression) and dplyr and ggplot
 
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R programming for beginners - This video is an introduction to R programming. I have another channel dedicated to R teaching: https://www.youtube.com/c/rprogramming101 In this video I provide a tutorial on some statistical analysis (specifically using the t-test and linear regression). I also demonstrate how to use dplyr and ggplot to do data manipulation and data visualisation. Its R programming for beginners really and is filled with graphics, quantitative analysis and some explanations as to how statistics work. If you’re a statistician, into data science or perhaps someone learning bio-stats and thinking about learning to use R for quantitative analysis, then you’ll find this video useful. Importantly, R is free. If you learn R programming you’ll have it for life. This video was sponsored by the University of Edinburgh. Find out more about their programmes at http://edin.ac/2pTfis2 This channel focusses on global health and public health - so please consider subscribing if you’re someone wanting to make the world a better place – I’d love to you join this community. I have videos on epidemiology, study design, ethics and many more.
Social Network Analysis with R | Examples
 
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Social network analysis with several simple examples in R. R file: https://goo.gl/CKUuNt Data file: https://goo.gl/Ygt1rg Includes, - Social network examples - Network measures - Read data file - Create network - Histogram of node degree - Network diagram - Highlighting degrees & different layouts - Hub and authorities - Community detection R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 24962 Bharatendra Rai
Transforming Data - Data Analysis with R
 
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This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 59827 Udacity
R: Exploratory Data Analysis (EDA), Univariate analysis
 
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One of the first steps to data analysis is to perform Exploratory Data Analysis. In this video we go over the basics of univariate data analysis, or analyzing each variable to better get to know our data. Here's the dataset used in this video: https://drive.google.com/open?id=0B67hcgV97X0mbnRYNzhYLU53X2c
Views: 5841 James Dayhuff
Why R - Data Analysis with R
 
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This video is part of an online course, Data Analysis with R. Check out the course here: https://www.udacity.com/course/ud651. This course was designed as part of a program to help you and others become a Data Analyst. You can check out the full details of the program here: https://www.udacity.com/course/nd002.
Views: 19632 Udacity
Introduction to R Data Analysis: Data Cleaning
 
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Data Cleaning and Dates using lubridate, dplyr, and plyr
Views: 48961 John Muschelli
R For Qualitative Analysis
 
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Introduction to R Tutorial to learn qualitative analysis package Word2Vec. Learn how to turn text into vectors and create a dendrogram and text map of your data. No prior coding experience necessary.
Views: 5848 Eren Kavvas
Data Analysis- Why use R
 
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Tim Young from CIC (Curtin Institute of Computation) talks about the use of R at the ‘Tools for Data Analysis: an overview of SPSS, NVivo , R and Python’ session that was held at Robertson Library on August 9th 2017. Learn about the tools available to assist with analysing your quantitative or qualitative data. This workshop was designed to help staff and postgraduate students use library resources effectively for research.
Views: 2196 Curtin Library
R Programming For Beginners | R Language Tutorial | R Tutorial For Beginners | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R Programming Tutorial For Beginners (R Tutorial Blog: https://goo.gl/mia382) will help you in understanding the fundamentals of R and will help you build a strong foundation in R. Below are the topics covered in this tutorial: 1. Variables 2. Data types 3. Operators 4. Conditional Statements 5. Loops 6. Strings 7. Functions Check out our R Playlist: https://goo.gl/huUh7Y Subscribe to our channel to get video updates. Hit the subscribe button above. #R #Rtutorial #Ronlinetraining #Rforbeginners #Rprogramming How it Works? 1. This is a 5 Week Instructor led Online Course, 30 hours of assignment and 20 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will be working on a real time project for which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - - - - About the Course Edureka's Data Analytics with R training course is specially designed to provide the requisite knowledge and skills to become a successful analytics professional. It covers concepts of Data Manipulation, Exploratory Data Analysis, etc before moving over to advanced topics like the Ensemble of Decision trees, Collaborative filtering, etc. During our Data Analytics with R Certification training, our instructors will help you: 1. Understand concepts around Business Intelligence and Business Analytics 2. Explore Recommendation Systems with functions like Association Rule Mining , user-based collaborative filtering and Item-based collaborative filtering among others 3. Apply various supervised machine learning techniques 4. Perform Analysis of Variance (ANOVA) 5. Learn where to use algorithms - Decision Trees, Logistic Regression, Support Vector Machines, Ensemble Techniques etc 6. Use various packages in R to create fancy plots 7. Work on a real-life project, implementing supervised and unsupervised machine learning techniques to derive business insights - - - - - - - - - - - - - - - - - - - Who should go for this course? This course is meant for all those students and professionals who are interested in working in analytics industry and are keen to enhance their technical skills with exposure to cutting-edge practices. This is a great course for all those who are ambitious to become 'Data Analysts' in near future. This is a must learn course for professionals from Mathematics, Statistics or Economics background and interested in learning Business Analytics. - - - - - - - - - - - - - - - - Why learn Data Analytics with R? The Data Analytics with R training certifies you in mastering the most popular Analytics tool. "R" wins on Statistical Capability, Graphical capability, Cost, rich set of packages and is the most preferred tool for Data Scientists. Below is a blog that will help you understand the significance of R and Data Science: Mastering R Is The First Step For A Top-Class Data Science Career Having Data Science skills is a highly preferred learning path after the Data Analytics with R training. Check out the upgraded Data Science Course For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Telegram: https://t.me/edurekaupdates
Views: 427960 edureka!
Exploratory data analysis 1
 
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Three R scripts showing some simple exploratory data analyses in R: contingency tables, histograms, boxplots/dotplots, and groupwise means.
Views: 31125 James Scott
Missing Data Analysis : Multiple Imputation in R
 
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Paper: Advanced Data Analysis Module: Missing Data Analysis : Multiple Imputation in R Content Writer: Souvik Bandyopadhyay
Views: 22972 Vidya-mitra
R Introduction: Data Analysis and Plotting
 
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This video uses a complex, yet not to large, data set to conduct a simple manipulation of data in R and RStudio. We will introduce data frames, matrices and variables. It demonstrates how to plot charts in R and how to gradually build them out of basic visual elements. The explanation will carefully avoid more complex statistical concepts. The data for this lesson can be obtained from (note different file name): * http://visanalytics.org/youtube-rsrc/r-data/Vic-2013-LGA-Profiles-NoPc.csv The source for the R code of this video can be found here (with some small discrepancies): * http://visanalytics.org/youtube-rsrc/r-intro/Demo-A2-Basic-Data-Analysis-and-Plotting.r Videos in data analytics and data visualization by Jacob Cybulski, visanalytics.org.
Views: 27525 ironfrown
Data Manipulation and Visualization with R | Examples using dplyr & ggplot2 Packages
 
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Data Manipulation and Visualization with R R File link: https://goo.gl/nRmkwr Data file: https://goo.gl/UMYMZR For fiftystater and colorplaner, run following lines: devtools::install_github("wmurphyrd/fiftystater") devtools::install_github("wmurphyrd/colorplaner") R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 8594 Bharatendra Rai
Statistics with R (1) - Linear regression
 
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In this video, I show how to use R to fit a linear regression model using the lm() command. I also introduce how to plot the regression line and the overall arithmetic mean of the response variable, and I briefly explain the use of diagnostic plots to inspect the residuals. Basic features of the R interface (script window, console window) are introduced. The R code used in this video is: data(airquality) names(airquality) #[1] "Ozone" "Solar.R" "Wind" "Temp" "Month" "Day" plot(Ozone~Solar.R,data=airquality) #calculate mean ozone concentration (na´s removed) mean.Ozone=mean(airquality$Ozone,na.rm=T) abline(h=mean.Ozone) #use lm to fit a regression line through these data: model1=lm(Ozone~Solar.R,data=airquality) model1 abline(model1,col="red") plot(model1) termplot(model1) summary(model1)
Views: 355903 Christoph Scherber
Analyze European survey data statistics in R (Rstudio)
 
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Prepare, clean, wrangle, and analyze political science data in R. Code and walkthrough for students or beginners learning quantitative, statistical analysis in R. This shows you how to do common data cleaning tasks, make a plot of country averages over time, and estimate a basic linear regression model with Eurobarometer data. How important is religion in different European countries? Which variables predict the probability individuals will vote in the European Parliament elections? Data for this script can be downloaded here: https://www.dropbox.com/s/5bdhel8l7c5r59z/eurobarometer_trends.dta?dl=0 The script can be found here: https://gist.github.com/jmrphy/9020745 Newsletter: https://tinyletter.com/jmrphy Blog: http://jmrphy.net/blog Twitter: http://twitter.com/jmrphy Podcast: http://jmrphy.libsyn.com/ Facebook: https://www.facebook.com/otherlifenow/ Periscope: https://www.pscp.tv/jstnmrphy Instagram: https://www.instagram.com/jstnmrphy/
Views: 4446 Justin Murphy
Linear Regression in R | Linear Regression in R With Example | Data Science Algorithms | Simplilearn
 
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This "Linear regression in R" video will help you understand what is linear regression, why linear regression, you will see how linear regression works using a simple example and you will also see a use case predicting the revenue of a company using linear regression. Linear Regression is the statistical model used to predict the relationship between independent and dependent variables by examining two factors. The first one is which variables, in particular, are significant predictors of the outcome variable and the second one is how significant is the regression line to make predictions with the highest possible accuracy. Now, lets deep dive into this video and understand what is linear regression. Below topics are explained in this "Linear Regression in R" video: 1. Why linear regression? ( 00:28 ) 2. What is linear regression? ( 03:09 ) 3. How linear regression works? ( 03:48 ) 4. Use case - Predicting the revenue using linear regression (10:05) To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 You can also go through the Slides here: https://goo.gl/HBso29 Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning Become an expert in data analytics using the R programming language in this data science certification training course. You’ll master data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language. With this data science course, you’ll get hands-on practice on R CloudLab by implementing various real-life, industry-based projects in the domains of healthcare, retail, insurance, finance, airlines, music industry, and unemployment. Why learn Data Science with R? 1. This course forms an ideal package for aspiring data analysts aspiring to build a successful career in analytics/data science. By the end of this training, participants will acquire a 360-degree overview of business analytics and R by mastering concepts like data exploration, data visualization, predictive analytics, etc 2. According to marketsandmarkets.com, the advanced analytics market will be worth $29.53 Billion by 2019 3. Wired.com points to a report by Glassdoor that the average salary of a data scientist is $118,709 4. Randstad reports that pay hikes in the analytics industry are 50% higher than IT The Data Science Certification with R has been designed to give you in-depth knowledge of the various data analytics techniques that can be performed using R. The data science course is packed with real-life projects and case studies, and includes R CloudLab for practice. 1. Mastering R language: The data science course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R. 2. Mastering advanced statistical concepts: The data science training course also includes various statistical concepts such as linear and logistic regression, cluster analysis and forecasting. You will also learn hypothesis testing. 3. As a part of the data science with R training course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and the Internet. Four additional projects are also available for further practice. The Data Science with R is recommended for: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields Learn more at: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Linear-Regression-in-R-2Sb1Gvo5si8&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn/ - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 12341 Simplilearn
Bayesian Inference in R
 
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How to do Bayesian inference with some sample data, and how to estimate parameters for your own data. It's easy! Link to datasets: http://www.indiana.edu/~kruschke/BEST/
Views: 42776 Andrew Jahn
Time Series Analysis with forecast Package in R Example Tutorial
 
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What is the difference between Autoregressive (AR) and Moving Average (MA) models? Explanation Video: https://www.youtube.com/watch?v=2kmBRH0caBA
Views: 24293 The Data Science Show
Introduction to Data Science with R - Data Analysis Part 3
 
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Part 3 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 67717 David Langer
Introduction to Data Science with R - Data Analysis Part 2
 
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Part 2 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including data exploration, data wrangling, data analysis, data visualization, feature engineering, and machine learning. All source code from videos are available from GitHub. NOTE - The data for the competition has changed since this video series was started. You can find the applicable .CSVs in the GitHub repo. Blog: http://daveondata.com GitHub: https://github.com/EasyD/IntroToDataScience I do Data Science training as a Bootcamp: https://goo.gl/OhIHSc
Views: 150421 David Langer
Data Science Projects Tutorial | Data Science Projects In R | Data Science Training | Edureka
 
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** Data Science Certification using R: https://www.edureka.co/data-science ** This Edureka "Data Science Projects" video explains how to solve a problem using data science and the basic approach of a Data Scientist to go about a problem. Below are the topics covered in this module: [01:30] Basic approach to solve a problem [02:21] Problem Statement 1 [02:56] Decision Trees and Random Forests [09:42] Problem Statement 2 [10:25] Logistic Regressions [21:44] Summary Check out our Data Science Tutorial blog series: http://bit.ly/data-science-blogs Check out our complete Youtube playlist here: http://bit.ly/data-science-playlist ------------------------------------- Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka #DataScienceProjects #DataScienceTutorial #MachineLearningProjects -------------------------------------- How it Works? 1. This is a 30-hour Instructor-led Online Course. 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training, you will be working on a real-time project for which we will provide you a Grade and a Verifiable Certificate! ------------------------------------- About the Course Edureka's Data Science Training lets you gain expertise in Machine Learning Algorithms like K-Means Clustering, Decision Trees, Random Forest, and Naive Bayes using R. Data Science Training encompasses a conceptual understanding of Statistics, Time Series, Text Mining and an introduction to Deep Learning. Throughout this Data Science Course, you will implement real-life use-cases on Media, Healthcare, Social Media, Aviation and HR. ------------------------------------- Who should go for this course? The market for Data Analytics is growing across the world and this strong growth pattern translates into a great opportunity for all the IT Professionals. Our Data Science Training helps you to grab this opportunity and accelerate your career by applying the techniques on different types of Data. It is best suited for: Developers aspiring to be a 'Data Scientist' Analytics Managers who are leading a team of analysts Business Analysts who want to understand Machine Learning (ML) Techniques Information Architects who want to gain expertise in Predictive Analytics 'R' professionals who wish to work Big Data Analysts wanting to understand Data Science methodologies ------------------------------------- Why learn Data Science? Data science is an evolutionary step in interdisciplinary fields like the business analysis that incorporate computer science, modelling, statistics and analytics. To take complete benefit of these opportunities, you need a structured training with an updated curriculum as per current industry requirements and best practices. Besides strong theoretical understanding, you need to work on various real-life projects using different tools from multiple disciplines to gather a data set, process and derive insights from the data set, extract meaningful data from the set, and interpret it for decision-making purposes. Additionally, you need the advice of an expert who is currently working in the industry tackling real-life data-related challenges. ------------------------------------- Got a question on the topic? Please share it in the comment section below and our experts will answer it for you. For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).
Views: 4806 edureka!
Introduction to R Programming for Excel Users
 
01:45:58
R programming is rapidly becoming a valuable skill for data professionals of all stripes and a must-have skill for aspiring data scientists. Adding R programming to your data analyst skillset allows you to leverage powerful data visualizations, statistical analyses, and even machine learning in your daily work. In this presentation, we illustrate how your knowledge of performing data analyses in Microsoft Excel gives you a unique foundation for quickly learning how to apply R in your daily work. No knowledge of R coding is required for this meetup as Dave will illustrate scenarios in Excel and then walk through how each Excel scenario is implemented in R. Attendees will learn how: • Fundamental concepts of Excel (e.g., working with tables, collections of cells, and functions) translate 100% to working with data in R. • Excel pivot tables translate to R code. • Creating charts in Excel is very similar to creating data visualizations in R. • R offers visualizations not available in Excel out of the box. An Excel spreadsheet and R code will be made available prior to the meetup via GitHub for attendees interested in following along during the talk. Repository: https://code.datasciencedojo.com/datasciencedojo/tutorials/tree/master/Business%20Data%20Analysis%20with%20Excel -- Learn more about Data Science Dojo here: https://hubs.ly/H0hC49J0 Watch the latest video tutorials here: https://hubs.ly/H0hC3hk0 See what our past attendees are saying here: https://hubs.ly/H0hC3jz0 -- Like Us: https://www.facebook.com/datasciencedojo/ Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/data-science-dojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo/ Vimeo: https://vimeo.com/datasciencedojo
Views: 37257 Data Science Dojo
R vs Python - What should I learn in 2019? | R and Python Comparison | Intellipaat
 
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This Intellipaat video on R vs Python provides you with a short and crisp introduction to top two languages used in the IT industry: R and Python. Some important parameters have been taken into consideration to give you R and Python comparison so that you understand how these languages differ from each other and also learn why one is preferred over the other in certain aspects. In this R vs Python video you will learn these: Brief of R- 0:28 Brief of Python- 0:48 Speed of both- 1:20 Code & Syntax- 1:39 variable Declaration- 1:48 Data handling Capability - 2:28 Deep Learning- 4:04 Percentage Switching- 4:53 Trends of R vs Python 2019- 5:09 Community Support- 5:26 Job Trends of R vs Python in 2019- 5:53 Which one to choose for Data Science? R or Python? - 6:32 #RvsPython #PythonvsR #RvsPythonDifferences Are you looking for something more? Enroll in our Python 3 certification training course and become a certified Python 3 Professional (https://goo.gl/EnbpgH). It is a 39 hrs instructor led training provided by Intellipaat which is completely aligned with industry standards and certification bodies. If you’ve enjoyed this Python vs R language video, Like us and Subscribe to our channel for more similar informative Python and R videos and free tutorials. What do you think which one of them is best language for data science? Tell us in the comment section below. ---------------------------- Intellipaat Edge 1. 24*7 Life time Access & Support 2. Flexible Class Schedule 3. Job Assistance 4. Mentors with +14 yrs 5. Industry Oriented Course ware 6. Life time free Course Upgrade ------------------------------ Why and who should watch this R vs Python for data science video? R and Python are one of the trending buzz in the IT industry. R is very popular in the IT industry on the other hand Python's popularity is continuously increasing. Seeing the demand for R and the increasing demand for Python, there might be a question in your mind like which one of them is better - R or Python? or which one should I learn R or Python in 2019? If these question have popped in your head too then this R vs Python comparison video is definitely for you. Why Python programming is important? This Python programming tutorial will show you how Python language has an elegant syntax, is easy to code, debug and run. You will learn Python is deployed across industry verticals by going through this video. Some of the main applications of Python are in Data Science, machine learning, statistical analysis, web development and web scraping. The Intellipaat Python tutorial is easy to understand, has real world Python examples and thus makes you understand why Python programming is so important and why you should learn Python and go for a Python career. Why should you opt for a Python career? If you want to fast-track your career then you should strongly consider Python. The reason for this is that it is one of the fastest growing and widely used programming languages. There is a huge demand for Python programmers. The salaries for Python programmers are very good. There is a huge growth opportunity in this domain as well. Why R programming is important? Because of it's extensible nature, R programming is finding higher adoption rates for Data Science specialization. It can be widely deployed for various applications and can be easily scaled.learning this r language will help you grab all those jobs that are being created at large companies offering very good pay scales. Why should you opt for an R programming career? It is one of the booming technologies in the market and hence R professionals are highly required by the companies. You will grab the best jobs in top MNCs after finishing this Intellipaat r programming online training. The entire Intellipaat r programming course is in line with the industry needs. There is a huge demand for r programming certified professional. The salaries for r programming professional are very good. Hence this Intellipaat R programming tutorial in 2019 is your stepping stone to a successful career! ------------------------------ For more Information: Please write us to [email protected], or call us at: +91- 7847955955 Website (Python): https://goo.gl/EnbpgH Website (R): https://bit.ly/2wlkPdF Facebook: https://www.facebook.com/intellipaatonline LinkedIn: https://www.linkedin.com/in/intellipaat/ Twitter: https://twitter.com/Intellipaat
Views: 8000 Intellipaat
Time Series Analysis - 1 | Time Series in Excel | Time Series Forecasting | Data Science|Simplilearn
 
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This Time Series Analysis (Part-1) tutorial will help you understand what is time series, why time series, components of time series, when not to use time series, why does a time series have to be stationary, how to make a time series stationary and at the end, you will also see a use case where we will forecast car sales for 5th year using the given data. Link to Time Series Analysis Part-2: https://www.youtube.com/watch?v=Y5T3ZEMZZKs You can also go through the slides here: https://goo.gl/RsAEB8 A time series is a sequence of data being recorded at specific time intervals. The past values are analyzed to forecast a future which is time-dependent. Compared to other forecast algorithms, with time series we deal with a single variable which is dependent on time. So, lets deep dive into this video and understand what is time series and how to implement time series using R. Below topics are explained in this " Time Series in R Tutorial " - 1. Why time series? 2. What is time series? 3. Components of a time series 4. When not to use time series? 5. Why does a time series have to be stationary? 6. How to make a time series stationary? 7. Example: Forecast car sales for the 5th year To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScienceWithPython #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning Become an expert in data analytics using the R programming language in this data science certification training course. You’ll master data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language. With this data science course, you’ll get hands-on practice on R CloudLab by implementing various real-life, industry-based projects in the domains of healthcare, retail, insurance, finance, airlines, music industry, and unemployment. Why learn Data Science with R? 1. This course forms an ideal package for aspiring data analysts aspiring to build a successful career in analytics/data science. By the end of this training, participants will acquire a 360-degree overview of business analytics and R by mastering concepts like data exploration, data visualization, predictive analytics, etc 2. According to marketsandmarkets.com, the advanced analytics market will be worth $29.53 Billion by 2019 3. Wired.com points to a report by Glassdoor that the average salary of a data scientist is $118,709 4. Randstad reports that pay hikes in the analytics industry are 50% higher than IT The Data Science Certification with R has been designed to give you in-depth knowledge of the various data analytics techniques that can be performed using R. The data science course is packed with real-life projects and case studies, and includes R CloudLab for practice. 1. Mastering R language: The data science course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R. 2. Mastering advanced statistical concepts: The data science training course also includes various statistical concepts such as linear and logistic regression, cluster analysis and forecasting. You will also learn hypothesis testing. 3. As a part of the data science with R training course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and the Internet. Four additional projects are also available for further practice. The Data Science with R is recommended for: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields Learn more at: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Time-Series-Analysis-gj4L2isnOf8&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn/ - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 35205 Simplilearn
Data Mining using R | Data Mining Tutorial for Beginners | R Tutorial for Beginners | Edureka
 
36:36
( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R tutorial on "Data Mining using R" will help you understand the core concepts of Data Mining comprehensively. This tutorial will also comprise of a case study using R, where you'll apply data mining operations on a real life data-set and extract information from it. Following are the topics which will be covered in the session: 1. Why Data Mining? 2. What is Data Mining 3. Knowledge Discovery in Database 4. Data Mining Tasks 5. Programming Languages for Data Mining 6. Case study using R Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #LogisticRegression #Datasciencetutorial #Datasciencecourse #datascience How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Website: https://www.edureka.co/data-science Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. " Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 81246 edureka!
Data Analytics For Beginners | Introduction To Data Analytics | Data Analytics Using R | Edureka
 
51:48
Data Analytics for R Course: https://www.edureka.co/r-for-analytics This Edureka Tutorial on Data Analytics for Beginners will help you learn the various parameters you need to consider while performing data analysis. The following are the topics covered in this session: 1:12 Introduction To Data Analytics 3:43 Statistics 14:32 Data Cleaning and Manipulation 16:00 Data Visualization 17:25 Machine Learning 18:28 Roles, Responsibilities and Salary of Data Analyst 19:53 Need of R 20:37 Hands-On Statistics for Data Science: https://youtu.be/oT87O0VQRi8 -------------------------- About the Master Program: Data Analytics Masters Program makes you proficient in tools and systems used by Data Analytics Professionals. It includes in-depth training on Statistics, Data Analytics with R, SAS, and Tableau. The curriculum has been determined by extensive research on 5000+ job descriptions across the globe. ------------------------------------- Prerequisites: There are no prerequisites for enrollment to the Masters Program. Whether you are an experienced professional working in the IT industry, or an aspirant planning to enter the world of Data Analyst, Masters Program is designed and developed to accommodate various professional backgrounds ---------------------------------------- Do subscribe to our channel and hit the bell icon to never miss an update from us in the future: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_lea... Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Got a question on the topic? Mention it in the comments section For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free).
Views: 19653 edureka!
Linear Regression Algorithm | Linear Regression in R | Data Science Training | Edureka
 
57:06
( Data Science Training - https://www.edureka.co/data-science ) This Edureka Linear Regression tutorial will help you understand all the basics of linear regression machine learning algorithm along with examples. This tutorial is ideal for both beginners as well as professionals who want to learn or brush up their Data Science concepts. Below are the topics covered in this tutorial: 1) Introduction to Machine Learning 2) What is Regression? 3) Types of Regression 4) Linear Regression Examples 5) Linear Regression Use Cases 6) Demo in R: Real Estate Use Case Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #LinearRegression #Datasciencetutorial #Datasciencecourse #datascience How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "
Views: 72926 edureka!
R - Sentiment Analysis and Wordcloud with R from Twitter Data | Example using Apple Tweets
 
23:01
Provides sentiment analysis and steps for making word clouds with r using tweets about apple obtained from Twitter. Link to R and csv files: https://goo.gl/B5g7G3 https://goo.gl/W9jKcc https://goo.gl/khBpF2 Topics include: - reading data obtained from Twitter in a csv format - cleaning tweets for further analysis - creating term document matrix - making wordcloud, lettercloud, and barplots - sentiment analysis of apple tweets before and after quarterly earnings report R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 21531 Bharatendra Rai
KNN Algorithm Using R | KNN Algorithm Example | Data Science Training | Edureka
 
24:59
** Data Science Certification using R: https://www.edureka.co/data-science ** This Edureka video on "KNN algorithm using R", will help you learn about the KNN algorithm in depth, you'll also see how KNN is used to solve real-world problems. Below are the topics covered in this module: (00:52) Introduction to Machine Learning (03:45) What is KNN Algorithm? (08:09) KNN Use Case (09:07) KNN Algorithm step by step (12:12) Hands - On (00:52) Introduction to Machine Learning (03:45) What is KNN Algorithm? (08:09) KNN Use Case (09:07) KNN Algorithm step by step (12:12) Hands - On Blog Series: http://bit.ly/data-science-blogs Data Science Training Playlist: http://bit.ly/data-science-playlist - - - - - - - - - - - - - - - - - Subscribe to our channel to get video updates. Hit the subscribe button above: https://goo.gl/6ohpTV Instagram: https://www.instagram.com/edureka_learning Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - - - - #knn #datasciencewithr #datasciencecourse #datascienceforbeginners #knnalgorithm #datasciencetraining #datasciencetutorial - - - - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data lifecycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modeling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyze Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyze data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies. For online Data Science training, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free) for more information.
Views: 6496 edureka!
Association Rules or Market Basket Analysis with R - An Example
 
10:43
Provides an example of steps involved in carrying out association rule analysis in R. Association rule analysis is also called market basket analysis or affinity analysis. Some examples of companies using this method include Amazon, Netflix, Ford, etc. Definitions for support, confidence and lift are also included. Also includes, - use of rules package and a priori function - reducing number of rules to manageable size by specifying parameter values - finding interesting and useful rules - finding and removing redundant rules - sorting rules by lift - visualizing rules using scatter plot, bubble plot and graphs R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 20106 Bharatendra Rai
Predictive Modelling Techniques | Data Science With R Tutorial
 
03:10:36
This lesson will teach you Predictive analytics and Predictive Modelling Techniques. Watch the New Upgraded Video: https://www.youtube.com/watch?v=DtOYBxi4AIE After completing this lesson you will be able to: 1. Understand regression analysis and types of regression models 2. Know and Build a simple linear regression model 3. Understand and develop a logical regression 4. Learn cluster analysis, types and methods to form clusters 5. Know more series and its components 6. Decompose seasonal time series 7. Understand different exponential smoothing methods 8. Know the advantages and disadvantages of exponential smoothing 9. Understand the concepts of white noise and correlogram 10. Apply different time series analysis like Box Jenkins, AR, MA, ARMA etc 11. Understand all the analysis techniques with case studies Regression Analysis: • Regression analysis mainly focuses on finding a relationship between a dependent variable and one or more independent variables. • It predicts the value of a dependent variable based on one or more independent variables • Coefficient explains the impact of changes in an independent variable on the dependent variable. • Widely used in prediction and forecasting Data Science with R Language Certification Training: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-r-tools-training?utm_campaign=Predictive-Analytics-0gf5iLTbiQM&utm_medium=SC&utm_source=youtube #datascience #datasciencetutorial #datascienceforbeginners #datasciencewithr #datasciencetutorialforbeginners #datasciencecourse The Data Science with R training course has been designed to impart an in-depth knowledge of the various data analytics techniques which can be performed using R. The course is packed with real-life projects, case studies, and includes R CloudLabs for practice. Mastering R language: The course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R. Mastering advanced statistical concepts: The course also includes the various statistical concepts like linear and logistic regression, cluster analysis, and forecasting. You will also learn hypothesis testing. As a part of the course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and Internet. R CloudLab has been provided to ensure a practical and hands-on experience. Additionally, we have four more projects for further practice. Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 217987 Simplilearn
Time Series In R | Time Series Forecasting | Time Series Analysis | Data Science Training | Edureka
 
34:00
( Data Science Training - https://www.edureka.co/data-science ) In this Edureka YouTube live session, we will show you how to use the Time Series Analysis in R to predict the future! Below are the topics we will cover in this live session: 1. Why Time Series Analysis? 2. What is Time Series Analysis? 3. When Not to use Time Series Analysis? 4. Components of Time Series Algorithm 5. Demo on Time Series For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 90741 edureka!
Ridge, Lasso & Elastic Net Regression with R | Boston Housing Data Example,  Steps & Interpretation
 
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Provides example with interpretations of applying Ridge, Lasso & Elastic Net Regression using Boston Housing data. R file: https://goo.gl/ywtVYg Machine Learning videos: https://goo.gl/WHHqWP Includes. - example with Boston housing data - illustrates use of caret package - data partition - custom control parameters - cross validation - linear model - residuals plot - use of glmnet package - ridge regression - plot results - log lambda plot - fraction deviance explained plot - variable importance plot - interpretation - lasso regression - elastic net regression - compare models - best model - saving and reading final model for later use - prediction R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 17450 Bharatendra Rai
Naive Bayes Classification with R | Example with Steps
 
14:55
Provides steps for applying Naive Bayes Classification with R. Data: https://goo.gl/nCFX1x R file: https://goo.gl/Feo5mT Machine Learning videos: https://goo.gl/WHHqWP Naive Bayes Classification is an important tool related to analyzing big data or working in data science field. R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 25316 Bharatendra Rai
Logistic Regression in R | Logistic Regression in R Example | Data Science Algorithms | Simplilearn
 
19:31
This "Logistic Regression in R" video will help you understand what is a regression, why regression, types of regression, why logistic regression, what is logistic regression and at the end, you will also see a use case implementation using logistic regression. Regression is a statistical relationship between two or more variables where a change in the independent variable is associated with a change in the dependent variable. Logistic Regression is used to estimate discrete values (usually binary values like 0/1) from a set of independent variables. It helps to predict the probability of an event by fitting data to a logit function. It is also called logit regression. Now, let us get started and understand how logistic regression works and implement it in R. Below topics are explained in this "Logistic Regression in R" video: 1. Why regression? ( 01:06 ) 2. What is regression? ( 03:24 ) 3. Types of regression ( 04:38 ) 4. Why logistic regression? ( 05:57 ) 5. What is logistic regression? ( 08:47 ) 6. Use case - College admission using logistic regression ( 11:53 ) To learn more about Data Science, subscribe to our YouTube channel: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 You can also go through the slides here: https://goo.gl/n1W24H Watch more videos on Data Science: https://www.youtube.com/watch?v=0gf5iLTbiQM&list=PLEiEAq2VkUUIEQ7ENKU5Gv0HpRDtOphC6 #DataScienceWithR #DataScienceCourse #DataScience #DataScientist #BusinessAnalytics #MachineLearning #DataScienceAlgorithms Become an expert in data analytics using the R programming language in this data science certification training course. You’ll master data exploration, data visualization, predictive analytics and descriptive analytics techniques with the R language. With this data science course, you’ll get hands-on practice on R CloudLab by implementing various real-life, industry-based projects in the domains of healthcare, retail, insurance, finance, airlines, music industry, and unemployment. Why learn Data Science with R? 1. This course forms an ideal package for aspiring data analysts aspiring to build a successful career in analytics/data science. By the end of this training, participants will acquire a 360-degree overview of business analytics and R by mastering concepts like data exploration, data visualization, predictive analytics, etc 2. According to marketsandmarkets.com, the advanced analytics market will be worth $29.53 Billion by 2019 3. Wired.com points to a report by Glassdoor that the average salary of a data scientist is $118,709 4. Randstad reports that pay hikes in the analytics industry are 50% higher than IT The Data Science Certification with R has been designed to give you in-depth knowledge of the various data analytics techniques that can be performed using R. The data science course is packed with real-life projects and case studies, and includes R CloudLab for practice. 1. Mastering R language: The data science course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R. 2. Mastering advanced statistical concepts: The data science training course also includes various statistical concepts such as linear and logistic regression, cluster analysis and forecasting. You will also learn hypothesis testing. 3. As a part of the data science with R training course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and the Internet. Four additional projects are also available for further practice. The Data Science with R is recommended for: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields Learn more at: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-sas-r-excel-training?utm_campaign=Logistic-Regression-in-R-XycruVLySDg&utm_medium=Tutorials&utm_source=youtube For more information about Simplilearn courses, visit: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn/ - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 14671 Simplilearn
How to do the Titanic Kaggle competition in R - Part 1
 
35:07
As part of submitting to Data Science Dojo's Kaggle competition you need to create a model out of the titanic data set. We will show you how to do this using RStudio. Titanic Data Set: https://www.kaggle.com/c/titanic Download RStudio: https://www.rstudio.com/products/rstudio -- Learn more about Data Science Dojo here: https://hubs.ly/H0hz71Q0 Watch the latest video tutorials here: https://hubs.ly/H0hz78h0 See what our past attendees are saying here: https://hubs.ly/H0hz72N0 -- At Data Science Dojo, we believe data science is for everyone. Our in-person data science training has been attended by more than 4000+ employees from over 800 companies globally, including many leaders in tech like Microsoft, Apple, and Facebook. -- Like Us: https://www.facebook.com/datasciencedojo Follow Us: https://twitter.com/DataScienceDojo Connect with Us: https://www.linkedin.com/company/datasciencedojo Also find us on: Google +: https://plus.google.com/+Datasciencedojo Instagram: https://www.instagram.com/data_science_dojo Vimeo: https://vimeo.com/datasciencedojo
Views: 56854 Data Science Dojo
Introduction To Exploratory Data Analysis | Business Analytics with R | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) Exploratory Data Analysis is an approach of analyzing data sets to summarize their main characteristics, often with visual methods. Promoted by John Tukey for encouraging statisticians to explore the data, EDA helps in identifying the outliers, trends, and patterns. Watch the video to learn about the following topics related to EDA: 1. Exploratory Data Analysis 2. Data Manipulation in R 3. Data Exploration in R 4. Boxplots and Histograms 5. Slicing and Dicing of data 6. Data Transformation and Aggregation for Analysis 7. Packages in R for Data Analysis 8. Common Analytical Mistakes Related Blogs: http://www.edureka.co/blog/why-should-a-statistical-professional-know-r/?utm_source=youtube&utm_medium=referral&utm_campaign=EDA http://www.edureka.co/blog/why-learn-r/?utm_source=youtube&utm_medium=referral&utm_campaign=EDA http://www.edureka.co/blog/importingspss-data-r/?utm_source=youtube&utm_medium=referral&utm_campaign=EDA Edureka is a New Age e-learning platform that provides Instructor-Led Live, Online classes for learners who would prefer a hassle free and self paced learning environment, accessible from any part of the world. The topics related to ‘Exploratory Data Analysis’ have extensively been covered in our course ‘Business Analytics with R’. For more information, please write back to us at [email protected] Call us at US: 1800 275 9730 (toll free) or India: +91-8880862004
Views: 24576 edureka!
ANOVA, ANOVA Multiple Comparisons & Kruskal Wallis in R | R Tutorial 4.9 | MarinStatsLectures|
 
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Analysis of Variance (ANOVA), Multiple Comparisons & Kruskal Wallis in R with Examples: Learn how to Conduct ANOVA in R, ANOVA Pairwise Comparisons in R, and Kruskal Wallis One-Way ANOVA in R with Examples! 👉🏼Related: ANOVA in Statistics & ANOVA in R Lecture Series: https://bit.ly/2Jb3uPr 📝 Find R practice dataset here: (https://statslectures.com/r-scripts-datasets ) 👍🏼Best Statistics & R Programming Language Tutorials: ( https://goo.gl/4vDQzT ) ►► Want to support us? You can Donate (https://bit.ly/2CWxnP2), Share Our Videos, Leave Comments or Give us a Like! In this Tutorial, you will learn to use various functions in R to: Conduct one-way analysis of variance (ANOVA) test in R, View ANOVA table in R, produce a visual display for the pair-wise comparisons of the analysis of variance in R, conduct multiple comparisons/ANOVA pair-wise comparisons in R, produce Kruskal-Wallis one-way analysis of variance using ranks with R Statistical Software. ■Table of Content 0:00:12 when should we use one-way analysis of variance (ANOVA) in statistics and in research 0:00:37 how to conduct ANOVA in R software using the "aov" command/function 0:00:42 how to access the help menu in R for ANOVA commands 0:00:52 how to create a boxplot in R statistical software 0:01:42 how to view ANOVA table in R using "summary" function 0:02:07 how to ask R for what is stored in an object using the "attributes" function. 0:02:23 how to extract certain attributes from an object in R using the dollar sign ($) 0:02:48 how to conduct multiple comparisons/pair-wise comparisons for the analysis of variance in R using the "TukeyHSD" command 0:03:17 how to produce a visual display for the pair-wise comparisons of the analysis of variance in R programming language using "plot" function 0:03:50 how to produce Kruskal-Wallis one-way analysis of variance using ranks in R using the "kruskal.test" function 0:03:56 when is it appropriate to use Kruskal-Wallis one-way analysis of variance for data in statistics and in research This video is a tutorial for programming in R Statistical Software for beginners, using RStudio. ▶︎▶︎ Watch More ▶︎ANOVA Use and Assumptions https://youtu.be/_VFLX7xJuqk ▶︎ Understanding the Sum of Squares in ANOVA, the concept of analysis of variance, and ANOVA hypothesis testing https://youtu.be/-AeU4y2vkIs ▶︎ ANOVA F Statistic and P-Value: https://youtu.be/k-xZzEYL8oc ▶︎ ANOVA & Bonferroni Multiple Comparisons Correction https://youtu.be/pscJPuCwUG0 ▶︎ Two Sample t-test in Statistics https://youtu.be/mBiVCrW2vSU ▶︎ Paired t-test in Statistics https://youtu.be/Q0V7WpzICI8 Follow MarinStatsLectures Subscribe: https://goo.gl/4vDQzT website: https://statslectures.com Facebook:https://goo.gl/qYQavS Twitter:https://goo.gl/393AQG Instagram: https://goo.gl/fdPiDn Our Team: Content Creator: Mike Marin (B.Sc., MSc.) Senior Instructor at UBC. Producer and Creative Manager: Ladan Hamadani (B.Sc., BA., MPH) These videos are created by #marinstatslectures to support some Statistics and R Programming courses at The University of British Columbia (UBC) (#IntroductoryStatistics and #RVideoTutorials for Health Science Research), although we make all videos available to the everyone everywhere for free. Thanks for watching! Have fun and remember that statistics is almost as beautiful as a unicorn! #rprogramming #statistics #Rstats
R vs Python | Best Programming Language for Data Science and Analysis | Edureka
 
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***** Python Online Training: https://www.edureka.co/python ***** ***** R Online Training: https://www.edureka.co/r-for-analytics ***** This Edureka video on R vs Python provides you with a short and crisp description of the top two languages used in Data Science and Data Analytics i.e. Python and R (Blog:http://bit.ly/2ClaowR). You will also see the head to head comparison between the two on various parameters and learn why one is preferred over the other in certain aspects. Following topics are covered in the video: 1:30 Various Aspects of Comparison 1:40 Speed 1:56 Legacy 2:13 Code 2:28 Databases 2:45 Practical Agility 3:10 Trends 3:31 Salary 4:25 Syntax Subscribe to our Edureka YouTube channel to get video updates: https://goo.gl/6ohpTV --------------------------------------------------------------------------------------------- Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka ------------------------------------------------------------------------------------------------ #PythonVsR #Python #R #Pythononlinetraining #Javaonlinetraining ----------------------------------------------------------------- For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 95440 edureka!
Logistic Regression with R: Categorical Response Variable at Two Levels (2018)
 
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Provides an example of student college application for carrying out logistic regression analysis with R. Data: https://goo.gl/VEBvwa R File: https://goo.gl/PdRktk Machine Learning videos: https://goo.gl/WHHqWP Includes, - use of a categorical binary output variable - data partition - logistic regression model - prediction - equation for prediction - misclassification errors for training and test data - confusion matrix for training and test data - goodness-of-fit test R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 30653 Bharatendra Rai
Introduction to Cluster Analysis with R - an Example
 
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Provides illustration of doing cluster analysis with R. R File: https://goo.gl/BTZ9j7 Machine Learning videos: https://goo.gl/WHHqWP Includes, - Illustrates the process using utilities data - data normalization - hierarchical clustering using dendrogram - use of complete and average linkage - calculation of euclidean distance - silhouette plot - scree plot - nonhierarchical k-means clustering Cluster analysis is an important tool related to analyzing big data or working in data science field. Deep Learning: https://goo.gl/5VtSuC Image Analysis & Classification: https://goo.gl/Md3fMi R is a free software environment for statistical computing and graphics, and is widely used by both academia and industry. R software works on both Windows and Mac-OS. It was ranked no. 1 in a KDnuggets poll on top languages for analytics, data mining, and data science. RStudio is a user friendly environment for R that has become popular.
Views: 114330 Bharatendra Rai
Data Partition with Oversampling in the R Software Example Tutorial
 
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1. Download the example data set: fitnessAppLog.csv https://drive.google.com/open?id=0Bz9Gf6y-6XtTczZ2WnhIWHJpRHc 2. Data Partition, Oversampling in the R Software Example Code: https://drive.google.com/open?id=13_EeM3neRu1QDSYx6myZoTQuEx7IHB8j
Views: 2290 The Data Science Show
Basic Analytical Techniques | Data Science With R Tutorial
 
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Basic Analytical Techniques Using R tools. After completing this course you will be able to: Watch the New Upgraded Video: https://www.youtube.com/watch?v=_WyUme_H2ZQ 1. Get a basic introduction to R 2. Understand exploration of data 3. Explore data using R 4. Visualize data using R 5. Understand diagnostic analytics 6. Implementing diagnostic analytics using R 7. Understand these concepts with the help of case studies Data Science with R Language Certification Training: https://www.simplilearn.com/big-data-and-analytics/data-scientist-certification-r-tools-training?utm_campaign=R-Language-Training-rqrrTfy-z-c&utm_medium=SC&utm_source=youtube #datascience #datasciencetutorial #datascienceforbeginners #datasciencewithr #datasciencetutorialforbeginners #datasciencecourse The Data Science with R training course has been designed to impart an in-depth knowledge of the various data analytics techniques which can be performed using R. The course is packed with real-life projects, case studies, and includes R CloudLabs for practice. Mastering R language: The course provides an in-depth understanding of the R language, R-studio, and R packages. You will learn the various types of apply functions including DPYR, gain an understanding of data structure in R, and perform data visualizations using the various graphics available in R. Mastering advanced statistical concepts: The course also includes the various statistical concepts like linear and logistic regression, cluster analysis, and forecasting. You will also learn hypothesis testing. As a part of the course, you will be required to execute real-life projects using CloudLab. The compulsory projects are spread over four case studies in the domains of healthcare, retail, and Internet. R CloudLab has been provided to ensure a practical and hands-on experience. Additionally, we have four more projects for further practice. Who should take this course? There is an increasing demand for skilled data scientists across all industries which makes this course suited for participants at all levels of experience. We recommend this Data Science training especially for the following professionals: 1. IT professionals looking for a career switch into data science and analytics 2. Software developers looking for a career switch into data science and analytics 3. Professionals working in data and business analytics 4. Graduates looking to build a career in analytics and data science 5. Anyone with a genuine interest in the data science field 6. Experienced professionals who would like to harness data science in their fields For more updates on courses and tips follow us on: - Facebook : https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn Get the android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 97923 Simplilearn