# Inferential Statistics

## Document Type

Book Chapter

## Publication Title

Indian Statistical Institute Series

## Abstract

The setup of inferential statistics is as follows. There is a population which is a set of all individuals or objects that we are interested in, but is too large to study in its entirety. Instead we obtain a random sample which is a subset of the population and use the information available in the subset to generalize to the population. Usually we specify a model for the probability distribution for the population. This is a probability density function (pdf) for continuous or probability mass function (pmf) for discrete distributions. Although the form of the distribution can be specified depending on the background information on the population, certain numerical characters may be unknown. These unknown but fixed numerical characteristics are associated with the model and are called parameters. A sample statistic is a numerical measure of a sample that can be calculated from the observations. The sample statistics are used to draw inference about population parameters.

## First Page

163

## Last Page

177

## DOI

10.1007/978-981-19-2008-0_13

## Publication Date

1-1-2023

## Recommended Citation

Sen, Rituparna and Das, Sourish, "Inferential Statistics" (2023). *Book Chapters*. 206.

https://digitalcommons.isical.ac.in/book-chapters/206