Statistics For Data Science And Business Analysis - Introduction

Types of data Measurement levels Graphs and tables; categorical variables Relationships between variables Measures of central tendency Measures of asymmetry Measures of variability Measures of the relationship between variables

Distributions Estimators and estimates Confidence intervals (interval estimator) Confidence interval for the difference of two means

Hypothesis testing is the heart of statistics. We start from the very basics: what are the null and alternative hypotheses. We show different examples and explain how to form the hypotheses that are later to be tested.

With the advancements in computing power, Regression Analysis became one of the leading methods for statistical inference. We introduce the concept and what is to come in the section.