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A comprehensive exploration of Statistics and Probability Theory concepts, with practical implementations in Python
A/B testing (or split-testing) is a randomized experiment with two variants A and B. It includes application of statistical hypothesis testing (or two-sample hypothesis testing), as used in the field of statistics. A/B testing is a way to compare two versions of a single variable, typically by testing a subject's response to variant A against variant B, and determining which of the two variants is more effective.
:chart_with_upwards_trend: :pushpin: This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical inference and use this information for making informed choices in analyzing data.
Google Advanced Data Analytics Projects: Automatidata, Waze, Tiktok and Salifort Motors
R programming and its application to data analysis and statistical methods
Repository for STATS projects
Data Science - Hypothesis Testing Work
Quick-reference guide to the 17 statistical hypothesis tests that you need in applied machine learning, with sample code in Python.