Performing Confirmatory Data Analysis in R

Offered By
Coursera Project Network
In this Guided Project, you will:

Understand the concepts of Confirmatory Data Analysis (CDA)

Perform different tests to illustrate the concepts of CDA

Explore built-in R dataset to test the hypothesis for more than two (2) independent samples

Clock2 hours
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

Welcome to this project-based course Performing Confirmatory Data Analysis in R. In this project, you will learn how to perform extensive confirmatory data analysis, which is similar to performing inferential statistics in R. By the end of this 2-hour long project, you will understand how to perform chi-square tests, which includes, the goodness of fit test, test for independence, and test for homogeneity. Also, you will learn how to calculate correlation for numeric variables and perform regression analysis. Also, you will learn how to interpret the results of a test and make viable decisions. By extension, you will learn how to explore some built-in R datasets to perform the different tests. Note, you do not need to be a data scientist or statistical analyst to be successful in this guided project, just a familiarity with basic statistics and performing hypothesis test in R suffice for this project. A fundamental prerequisite is having a good understanding of the theory of hypothesis test. So, I recommend that you should take the Hypothesis Testing in R project before taking this project.

Skills you will develop

Statistical InferenceStatistical Hypothesis TestingRegression AnalysisAnalysis Of Variance (ANOVA)

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Getting Started

  2. Chi-square tests: Goodness of fit test

  3. Chi-square tests: Test for Independence

  4. Chi-square tests: Test for Homogeneity

  5. Correlation

  6. Regression

  7. Analysis of Variance (ANOVA) - Part I

  8. Analysis of Variance (ANOVA) - Part II

  9. The Kruskal-Wallis test

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.