Inferential statistics allows us to draw conclusions from data that might not be immediately obvious. This course focuses on enhancing your ability to develop hypotheses and use common tests such as t-tests, ANOVA tests, and regression to validate your claims.
Estimate population parameters from sample statistics using confidence intervals.,Estimate the effect of a treatment.
How to determine if a treatment has changed the value of a population parameter.
How to test the effect of a treatment.,Compare the difference in means for two groups when there are small sample sizes.
Learn how to test whether or not there are differences between three or more groups.
Learn how to describe and test the strength of a relationship between two variables.
How changes in one variable are related to changes in a second variable.
Learn how to compare and test frequencies for categorical data.
Pushkar Dk completed this course, spending 7 hours a week on it and found the course difficulty to be medium.
A very good second course on elementary statistics. It requires us to finish 'descriptive statistics' before starting it and is a much lengthier course. However, the teaching style is very nice with emphasis on "why?" rather than simply calculating variables without understanding the concepts. The lecturers go to great lengths to help us visualize the data as well (I've come to believe that any course from Katie Kormanik must be easy to understand)!
Deepal D'silva completed this course, spending 4 hours a week on it and found the course difficulty to be medium.
This is an excellent course for intermediate statistics. This course builds upon the Descriptive statistics course. The method of teaching focuses on understanding and applying various concepts rather than just plugging values in formulas.