Inferential Statistics
This course is part of Data Analysis with R Specialization
Instructor: Mine Çetinkaya-Rundel
Skills you'll gain
There are 5 modules in this course
This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data
Central Limit Theorem and Confidence Interval
Inference and Significance
Inference for Comparing Means
Inference for Proportions
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