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
About this Course
Skills you will gain
- Statistical Inference
- Statistical Hypothesis Testing
- R Programming
Syllabus - What you will learn from this course
About the Specialization and the Course
Central Limit Theorem and Confidence Interval
Inference and Significance
Inference for Comparing Means
- 5 stars83.10%
- 4 stars13.31%
- 3 stars1.92%
- 2 stars0.63%
- 1 star1.02%
TOP REVIEWS FROM INFERENTIAL STATISTICS
I learnt a lot about inferential statistics from this course. It help me to understand better why I used one inferential method instead of another, and the assumptions and conditions.
Very nicely designed course and it also progresses very well. If higher mathematics would be involved in it, the course has the ability to replace many college's statistical inference's classes.
Great course. If you put in a little effort, you will come out with a lot of new knowledge. I recommend using the book after you have seen the movies. It gives a deeper picture of how it works. Great!
Very well taught. Student given an opportunity to explore and search for ways to solve problems by themselves. Professor (mentor) and other students always ready to help should you get stuck!
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Can I just enroll in a single course? I'm not interested in the entire Specialization.
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