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Search results “Statistical analysis of data example”

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Seven different statistical tests and a process by which you can decide which to use. The tests are: Test for a mean, test for a proportion, difference of proportions, difference of two means - independent samples, difference of two means - paired, chi-squared test for independence and regression. This video draws together videos about Helen, her brother, Luke and the choconutties.
Views: 675662 Dr Nic's Maths and Stats

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This statistical analysis overview explains descriptive and inferential statistics. Watch more at http://www.lynda.com/Excel-2007-tutorials/business-statistics/71213-2.html?utm_medium=viral&utm_source=youtube&utm_campaign=videoupload-71213-0101 This specific tutorial is just a single movie from chapter one of the Excel 2007: Business Statistics course presented by lynda.com author Curt Frye. The complete Excel 2007: Business Statistics course has a total duration of 4 hours and 19 minutes and covers formulas and functions for calculating averages and standard deviations, charts and graphs for summarizing data, and the Analysis ToolPak add-in for even greater insights into data Excel 2007: Business Statistics table of contents: Introduction 1. Introducing Statistics 2. Learning Useful Excel Techniques 3. Summarizing Data Using Tables and Graphics 4. Describing Data Using Numerical Methods 5. Using Probability Distributions 6. Sampling Values from a Population 7. Testing Hypotheses 8. Using Linear and Multiple Regression Conclusion

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The kind of graph and analysis we can do with specific data is related to the type of data it is. In this video we explain the different levels of data, with examples. Subtitles in English and Spanish.
Views: 780908 Dr Nic's Maths and Stats

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Copyright Broad Institute, 2013. All rights reserved. The presentation above was filmed during the 2012 Proteomics Workshop, part of the BroadE Workshop series. The Proteomics Workshop provides a working knowledge of what proteomics is and how it can accelerate biologists' and clinicians' research. The focus of the workshop is on the most important technologies and experimental approaches used in modern mass spectrometry (MS)-based proteomics.

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Presenter: Christopher Fonnesbeck Description This tutorial will introduce the use of Python for statistical data analysis, using data stored as Pandas DataFrame objects. Much of the work involved in analyzing data resides in importing, cleaning and transforming data in preparation for analysis. Therefore, the first half of the course is comprised of a 2-part overview of basic and intermediate Pandas usage that will show how to effectively manipulate datasets in memory. This includes tasks like indexing, alignment, join/merge methods, date/time types, and handling of missing data. Next, we will cover plotting and visualization using Pandas and Matplotlib, focusing on creating effective visual representations of your data, while avoiding common pitfalls. Finally, participants will be introduced to methods for statistical data modeling using some of the advanced functions in Numpy, Scipy and Pandas. This will include fitting your data to probability distributions, estimating relationships among variables using linear and non-linear models, and a brief introduction to Bayesian methods. Each section of the tutorial will involve hands-on manipulation and analysis of sample datasets, to be provided to attendees in advance. The target audience for the tutorial includes all new Python users, though we recommend that users also attend the NumPy and IPython session in the introductory track. Tutorial GitHub repo: https://github.com/fonnesbeck/statistical-analysis-python-tutorial Outline Introduction to Pandas (45 min) Importing data Series and DataFrame objects Indexing, data selection and subsetting Hierarchical indexing Reading and writing files Date/time types String conversion Missing data Data summarization Data Wrangling with Pandas (45 min) Indexing, selection and subsetting Reshaping DataFrame objects Pivoting Alignment Data aggregation and GroupBy operations Merging and joining DataFrame objects Plotting and Visualization (45 min) Time series plots Grouped plots Scatterplots Histograms Visualization pro tips Statistical Data Modeling (45 min) Fitting data to probability distributions Linear models Spline models Time series analysis Bayesian models Required Packages Python 2.7 or higher (including Python 3) pandas 0.11.1 or higher, and its dependencies NumPy 1.6.1 or higher matplotlib 1.0.0 or higher pytz IPython 0.12 or higher pyzmq tornado
Views: 70889 Enthought

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Download files: http://people.highline.edu/mgirvin/excelisfun.htm Topics in this video: 1. (00:43) Categorical Data vs. Quantitative Data 2. (02:00) Scales of Measurement (Levels of Measurement): Nominal, Ordinal, Interval, Ratio 3. (14:42) Cross Sectional Data vs. Time Series Data 4. (15:48) Graphical Display of types of Data 5. (16:22) How to Enter Data into the spreadsheet and use the Auto Complete (Auto Text) to your benefit 6. (18:50) How to create a new Excel Workbook to do your Homework from the Textbook
Views: 32763 ExcelIsFun

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Views: 4124 Lyndsey Sales

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Views: 16221 S Manikandan

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Get the full course at: http://www.MathTutorDVD.com The student will learn the big picture of what a hypothesis test is in statistics. We will discuss terms such as the null hypothesis, the alternate hypothesis, statistical significance of a hypothesis test, and more. In this step-by-step statistics tutorial, the student will learn how to perform hypothesis testing in statistics by working examples and solved problems.
Views: 1083159 mathtutordvd

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Views: 68502 David Russell

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A step-by-step approach for choosing an appropriate statistcal test for data analysis.

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There is a growing interest from the Oil and Gas industry in the application of statistical analysis methods in the integrity management of assets. A major area of application is statistical analysis in the planning and evaluation of inspections carried on out equipment where there is potential for in-service degradation. This area is of growing relevance as operators seek to more effectively manage the risks associated with in-service degradation and developments in inspection technology make available more quantitative information. Statistical analysis allows an improved understanding of asset condition, taking into consideration the capability and limitations of the inspection methods, and this leads to improved decision making. There are substantial benefits to operators with respect to risk management and business performance. A major area of application of statistical analysis is in the planning and evaluation of sampling inspections where coverage is less than 100%. The aim of sampling inspections is to obtain sufficient information to allow reliable estimates for the regions not inspected. Statistical analysis underpins sampling approaches, in providing the basis for estimates for the uninspected area and also in assessing the reliability of the estimates. Statistical analysis in support of sampling inspection is now widely applied in practice - it is for example a fundamental requirement of NII of pressure vessels where a Type B strategy per the HOIS Recommended Practice for NII (DNV-RP-G103) applies. This free webinar will give attendees an overview of statistical analysis as applied to planning and evaluations of inspections in support of integrity management of process equipment. The webinar covers the following topics. -Introduction to application of statistical methods in integrity management -Statistical characteristics of in-service corrosion Basic theory covering extreme value analysis (EVA) and use of wall thickness distributions -Planning for effective sample inspections -Key inspection parameters, including coverage, accuracy and probability of detection -Use of statistical analysis for Type B NII cases -Example applications and case studies Your presenter: Mark Stone Bsc Eng (Mech), PhD Mark is responsible for Sonomatic?s integrity support area and leads a team delivering integrity-related services to clients. He is a Mechanical Engineer with over 25 years experience of working closely with NDT inspection colleagues to ensure better integration of inspection as part of more effective integrity management approaches. His experience covers planning for reliable inspection approaches and assessment of inspection results from an integrity perspective. A major part of his role covers development of methods to ensure best use is made of inspection data as input to integrity management decision making. This addresses a wide range of applications where statistical analysis is used for planning and evaluation of limited coverage inspections. Examples include development of strategies for non-intrusive inspection of pressure vessels, storage tanks, processing piping and unpiggable pipelines. He is primary author of the HOIS Recommended Practices for Non-intrusive inspection (NII) and Statistical Analysis of Inspection Data. http://www.sonomatic.com/index.php?page=webinars&objectid=674
Views: 446 Sonomatic

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This tutorial provides an overview of statistical analyses in the social sciences. It distinguishes between descriptive and inferential statistics, discusses factors for choosing an analysis procedure, and identifies the difference between parametric and nonparametric procedures.
Views: 214744 The Doctoral Journey

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Use simple data analysis techniques in SPSS to analyze survey questions.
Views: 789285 Claus Ebster

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Views: 1416 Kunchok Dorjee

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An explanation of how to compute the chi-squared statistic for independent measures of nominal data. For an explanation of significance testing in general, see http://evc-cit.info/psych018/hyptest/index.html There is also a chi-squared calculator at http://evc-cit.info/psych018/chisquared/index.html
Views: 860373 J David Eisenberg

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Qualitative research is a strategy for systematic collection, organization, and interpretation of phenomena that are difficult to measure quantitatively. Dr. Leslie Curry leads us through six modules covering essential topics in qualitative research, including what it is qualitative research and how to use the most common methods, in-depth interviews and focus groups. These videos are intended to enhance participants' capacity to conceptualize, design, and conduct qualitative research in the health sciences. Welcome to Module 5. Bradley EH, Curry LA, Devers K. Qualitative data analysis for health services research: Developing taxonomy, themes, and theory. Health Services Research, 2007; 42(4):1758-1772. Learn more about Dr. Leslie Curry http://publichealth.yale.edu/people/leslie_curry.profile Learn more about the Yale Global Health Leadership Institute http://ghli.yale.edu
Views: 144930 YaleUniversity

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Views: 2438 AUBGTalks

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R programming for beginners - This video is an introduction to R programming in which 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.

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Exploring some basic data analysis in excel
Views: 43181 Jon Jasinski

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Views: 37155 Tom Gallagher

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Download files: http://people.highline.edu/mgirvin/excelisfun.htm Topics in this video: 1. (00:21) What Is / Are Statistics? Define Statistics 2. (02:42) Descriptive Statistics and Inferential Statistics 3. (05:00) Collect, analyze and present raw data on Yahoo Stock Price: Search the internet, download, create formulas and crate a Chart and present the information in a useful way. 4. (06:05) Get Data from http://finance.yahoo.com/ 5. (06:43) Copy and paste data from internet into an Excel spreadsheet. Learn about Paste Special, Text 6. (07:28) Download a “.csv” file. “.csv” and “.txt” file types (file extensions) are text files. When you open them, they look like Excel, but it is not. We can copy and paste into a real Excel file. Text files are common files types that allow raw data to be transferred from one system to another. Text files are intermediate steps between the original Database and your Excel Spreadhseet. 7. (07:46) Control Panel, Folder Options, View Tab, Uncheck “Hide extensions for known file types” 8. (08:47) Highlight whole table keyboard is Ctrl + * 9. (09:50) Calculate maximum stock price with MAX function, minimum stock price with MIN and Mean using the AVERAGE function. 10. (11:30) Keyboard shortcuts for highlighting ranges that are not next to each other (noncontiguous ranges): Ctrl + Mouse Click 11. (12:15) Create Line Chart from Historical Data 12. (13:58) Page Setup 13. (17:52) Example of Inferential Statistics
Views: 37048 ExcelIsFun

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Let's go on a journey through univariate analysis and learn about descriptive statistics in research!
Views: 44181 ChrisFlipp

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Analysis is often done as duplicates. The error seen within the duplicates is a handle on overall errors. I was in a research group that developed this technique.
Views: 1403 mrphysh

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Let's learn about Chi-square, t-test, and ANOVA!
Views: 35396 ChrisFlipp

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Views: 125904 CS Dojo

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Statistical Analysis of Data by Dr.Shahid,PhD - Research and Thesis Subscribe this channel and follow all the video in the playlist.If you are currently doing any research or writing a thesis please follow step by step guidelines provided in these videos hope you will get a good supervision of your quality research. quantitative research, quantitative research methods, quantitative research designs, quantitative research in urdu, quantitative research in nursing, quantitative research presentation, quantitative research example, quantitative research designs descriptive non-experimental, quantitative research vs qualitative, quantitative research questions, fundamental research, fundamental reggae jimmy cliff, fundamental review of the trading book, fundamental reggae, fundamental research in hindi, fundamental results, reading fundamental, fundamental and realized niche, fundamental rights (review i), fundamental 5 recognize and reinforce, how to write a good research paper, how to write a good resume, how to write a good research proposal, how to write a good resignation letter, how to write a good research question, how to write a good resume with no job experience, how to write a good resume and cover letter, how to write a good research essay, how to write a good resume 2016, how to write a good research, how to write a good proposal, how to write a good problem statement, how to write a good project, how to write a good profile, how to write a good protagonist, how to write a good program, how to write a good product review, how to write a good research proposal, how to write a good dating profile, how to write a good business proposal, how to write research paper, how to write research proposal, how to write research paper in urdu, how to write research article, how to write research methodology, how to write research paper in computer science, I how to write research thesis, a how to write research report, how to write research paper in latex, how to write research objectives,
Views: 243 Research and Thesis

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Amir H. Ghaseminejad explains an example for designing a process consistant with six sigma strategy.

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Tutorial introducing the idea of linear regression analysis and the least square method. Typically used in a statistics class. Playlist on Linear Regression http://www.youtube.com/course?list=ECF596A4043DBEAE9C Like us on: http://www.facebook.com/PartyMoreStudyLess Created by David Longstreet, Professor of the Universe, MyBookSucks http://www.linkedin.com/in/davidlongstreet
Views: 629966 statisticsfun

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Statistical Analysis and Data Mining This webinar discuss the ability to analysis statistical performance information from historical market data based on any trading indicator or concept.

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This video is part of the University of Southampton, Southampton Education School, Digital Media Resources http://www.southampton.ac.uk/education http://www.southampton.ac.uk/~sesvideo/

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Watch Sample Class recording: http://www.edureka.co/statistics-essentials-for-analytics?utm_source=youtube&utm_medium=referral&utm_campaign=statistics-tut-1 Statistics is the study of the collection, analysis, interpretation, presentation, and organization of data.In applying statistics to, e.g., a scientific, industrial, or societal problem, it is conventional to begin with a statistical population or a statistical model process to be studied. Populations can be diverse topics such as "all persons living in a country" or "every atom composing a crystal". Statistics deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments. The video covers following topics: 1.Exploratory Analysis 2.Few termenologie son Statstics 3.Variance 4.Standard Deviation 5.Inquartile Range 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 Statistics & Probability have extensively been covered in our course 'Statistics Essentials for Analytics’. 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: 77122 edureka!

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Likert Scale: http://en.wikipedia.org/wiki/Likert_scale R: http://www.r-project.org/
Views: 200180 Alan Cann

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This is just a few minutes of a complete course. Get full lessons & more subjects at: http://www.MathTutorDVD.com. In this lesson we will cover the difference between descriptive and inferential statistics.
Views: 70176 mathtutordvd

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Updated video 2018: SPSS for Beginners - Introduction https://youtu.be/_zFBUfZEBWQ This video provides an introduction to SPSS/PASW. It shows how to navigate between Data View and Variable View, and shows how to modify properties of variables.
Views: 1349058 Research By Design

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Basic introduction to correlation - how to interpret correlation coefficient, and how to chose the right type of correlation measure for your situation. 0:00 Introduction to bivariate correlation 2:20 Why does SPSS provide more than one measure for correlation? 3:26 Example 1: Pearson correlation 7:54 Example 2: Spearman (rhp), Kendall's tau-b 15:26 Example 3: correlation matrix I could make this video real quick and just show you Pearson's correlation coefficient, which is commonly taught in a introductory stats course. However, the Pearson's correlation IS NOT always applicable as it depends on whether your data satisfies certain conditions. So to do correlation analysis, it's better I bring together all the types of measures of correlation given in SPSS in one presentation. Watch correlation and regression: https://youtu.be/tDxeR6JT6nM ------------------------- Correlation of 2 rodinal variables, non monotonic This question has been asked a few times, so I will make a video on it. But to answer your question, monotonic means in one direction. I suggest you plot the 2 variables and you'll see whether or not there is a monotonic relationship there. If there is a little non-monotonic relationship then Spearman is still fine. Remember we are measuring the TENDENCY for the 2 variables to move up-up/down-down/up-down together. If you have strong non-monotonic shape in the plot ie. a curve then you could abandon correlation and do a chi-square test of association - this is the "correlation" for qualitative variables. And since your 2 variables are ordinal, they are qualitative. Good luck
Views: 493883 Phil Chan

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Views: 35971 ExcelIsFun

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Eirik Helno Herø and Cansu Birgen Virtual Simulation Lab seminar series http://www.virtualsimlab.com

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Excel file: https://dl.dropboxusercontent.com/u/561402/TTEST.xls In this video Paul Andersen explains how to run the student's t-test on a set of data. He starts by explaining conceptually how a t-value can be used to determine the statistical difference between two samples. He then shows you how to use a t-test to test the null hypothesis. He finally gives you a separate data set that can be used to practice running the test. Do you speak another language? Help me translate my videos: http://www.bozemanscience.com/translations/ Music Attribution Intro Title: I4dsong_loop_main.wav Artist: CosmicD Link to sound: http://www.freesound.org/people/CosmicD/sounds/72556/ Creative Commons Atribution License Outro Title: String Theory Artist: Herman Jolly http://sunsetvalley.bandcamp.com/track/string-theory All of the images are licensed under creative commons and public domain licensing: 1.3.6.7.2. Critical Values of the Student’s-t Distribution. (n.d.). Retrieved April 12, 2016, from http://www.itl.nist.gov/div898/handbook/eda/section3/eda3672.htm File:Hordeum-barley.jpg - Wikimedia Commons. (n.d.). Retrieved April 11, 2016, from https://commons.wikimedia.org/wiki/File:Hordeum-barley.jpg Keinänen, S. (2005). English: Guinness for strenght. Retrieved from https://commons.wikimedia.org/wiki/File:Guinness.jpg Kirton, L. (2007). English: Footpath through barley field. A well defined and well used footpath through the fields at Nuthall. Retrieved from https://commons.wikimedia.org/wiki/File:Footpath_through_barley_field_-_geograph.org.uk_-_451384.jpg pl.wikipedia, U. W. on. ([object HTMLTableCellElement]). English: William Sealy Gosset, known as “Student”, British statistician. Picture taken in 1908. Retrieved from https://commons.wikimedia.org/wiki/File:William_Sealy_Gosset.jpg The T-Test. (n.d.). Retrieved April 12, 2016, from http://www.socialresearchmethods.net/kb/stat_t.php
Views: 384127 Bozeman Science

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In this video Dr. Ziene Mottiar, DIT, discusses issues around analyzing data and writing the analysing chapter. The difference between Findings and Analysis chapters is also discussed. This video is useful for anyone who is writing a dissertation or thesis.
Views: 64171 ZieneMottiar

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For more, visit http://www.statscast.net This video explains the purpose of t-tests, how they work, and how to interpret the results.
Views: 653070 StatsCast

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statisticslectures.com - where you can find free lectures, videos, and exercises, as well as get your questions answered on our forums!
Views: 349950 statslectures

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It is a Statistical software that is used to analyze any agricultural data. It is a 32-bit operating system software no update version is available in internet. Here you get how to analysis statistical data and how to make ANOVA table. Facebook: https://www.facebook.com/dhiman.adhikary.5 If you want to analysis your data , please message me. The cost will be depend on your data.

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Views: 12628 Great Learning

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This video describes five common methods of sampling in data collection. Each has a helpful diagrammatic representation. You might like to read my blog: https://creativemaths.net/blog/
Views: 674911 Dr Nic's Maths and Stats

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