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Performing Confirmatory Data Analysis in R

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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.

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Discover the essentials of confirmatory data analysis in R with this engaging 2-hour project-based course. Guided by an expert instructor, you'll master chi-square tests, correlation calculations, and regression analysis, all while interpreting test results for informed decision-making. Ideal for those with basic statistics knowledge, this professional-level course offers hands-on experience with R's built-in datasets. Available through Coursera's Starter subscription, it's perfect for data enthusiasts looking to deepen their analytical skills.