Follow

Inferential Statistics

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



Career Relevance by Data Role

The techniques and tools covered in Inferential Statistics are most similar to the requirements found in Business Analyst job advertisements.


Similarity Scores (Out of 100)

Fast Facts

Tools
R RStudio

Techniques
Data Analysis Data Sets Distributions Inference Significance Statistical Analysis Confidence Intervals

Similar Opportunities
Statistics and R

EdX - Harvard University

Quantitative Methods

Coursera - University of Amsterdam