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  1.2. Basic statistical concepts Population A population is the entire group of individuals, objects, or events that we are interested in studying. It is often too difficult or expensive to study an entire population, so we usually select a sample from the population. For example, let's say we are interested in studying the average height of all women in India. The population in this case would be all women in India. Examples: All registered voters in India All iPhone users in the world All students enrolled in a university Sample A sample is a subset of the population that we observe and collect data from. In the previous example, it would be impossible to measure the height of every single woman in India, so we would instead measure the height of a sample of women. For instance, we could measure the height of 1,000 randomly selected women from across India and use that information to make inferences about the population. Then we can say 1,000 is the sample siz...

  Chapter 1: Introduction to Statistics Overview of Statistics and its applications in data science Basic statistical concepts: population, sample, variable, data types, and measures of central tendency and dispersion Sampling techniques and sampling distributions 1.1 Overview of statistics and its applications in data science Statistics is a branch of mathematics that deals with the collection, analysis, interpretation, presentation, and organization of data. It is an important tool in data science, which involves the extraction of insights and knowledge from data using various techniques and algorithms. Statistics is used in various stages of the data science workflow, including data pre-processing, exploratory data analysis, feature engineering, model training and evaluation, and interpretation of results. It provides a framework for making sense of data, identifying patterns, relationships, and drawing conclusions based on evidence. Some of the...