Simple Statistics

Data Science Statistics : Data Science from Scratch for Beginners : Data Analysis Techniques, Method Course : Analytics.

A quick and easy guide on statistical regression for machine learning

This book describes the probability theory associated with frequently used statistical procedures and the relation between probability theory and statistical inference. The first third of the book is dedicated to probability theory including topics relating to events, random variables, and the Central Limit Theorem. Statistical topics then include parameter estimation with confidence intervals, hypothesis testing, chi-square tests, t tests, and several non-parametric tests. Flow charts are frequently used to facilitate an understanding of the material considered. The examples and problems in the book all concern simple data sets which can be analyzed with a simple calculator; however, the R code required to complete many examples and problems is provided as well for those that are interested.

Statistics is often regarded as a boring, and therefore difficult, subject particularly by those whose previous experience has not produced any real need to understand variation and to make appropriate allowances for it. The subject can certainly be presented in a boring way and in much advanced work can be conceptually and mathematically very difficult indeed.

From basics to multiple regression