What is the purpose of inferential statistics?

The purpose of inferential statistics is to make inferences about a population based on sample data. This involves using data collected from a smaller group (the sample) to draw conclusions or make predictions about a larger group (the population). Inferential statistics are crucial when it is impractical or impossible to collect data from every individual in a population.

Methods such as hypothesis testing, confidence intervals, and regression analysis fall under inferential statistics, allowing researchers to assess relationships and make predictions while accounting for randomness and uncertainty. This is distinct from descriptive statistics, which focuses on summarizing and presenting the data collected without making predictions or inferences about a larger population. Understanding this distinction is key to grasping how researchers use statistical methods to interpret data and make informed conclusions based on sample information.