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Search results “R data analysis examples”

27:20
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

01:21:50
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

25:56
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

01:33:00
Views: 538003 edureka!

07:22
Tutorial on importing data into R Studio and methods of analyzing data.
Views: 198660 MrClean1796

15:49
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.

26:25
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

03:01
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

30:01
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

01:29
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

01:04:00
Data Cleaning and Dates using lubridate, dplyr, and plyr
Views: 48961 John Muschelli

30:37
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

07:31
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

01:10:56
Views: 427960 edureka!

30:31
Views: 17050 Spark Summit

27:40
Three R scripts showing some simple exploratory data analyses in R: contingency tables, histograms, boxplots/dotplots, and groupwise means.
Views: 31125 James Scott

14:22
Paper: Advanced Data Analysis Module: Missing Data Analysis : Multiple Imputation in R Content Writer: Souvik Bandyopadhyay
Views: 22972 Vidya-mitra

14:15
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

24:07
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

19:22
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

13:09
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

30:32
Views: 12341 Simplilearn

09:30
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

31:04
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

55:33
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

59:48
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

22:43
Views: 4806 edureka!

01:45:58
Views: 37257 Data Science Dojo

08:15
Views: 8000 Intellipaat

32:49
Views: 35205 Simplilearn

08:56
Views: 43639 Prabhudev Konana

36:36
Views: 81246 edureka!

51:48
Views: 19653 edureka!

57:06
Views: 72926 edureka!

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

24:59
Views: 6496 edureka!

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

03:10:36
Views: 217987 Simplilearn

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!

28:54
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

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

19:31
Views: 14671 Simplilearn

35:07
Views: 56854 Data Science Dojo

01:00:05
( 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!

04:37
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

07:19
Views: 95440 edureka!

19:47
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

18:11
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

20:07