Descriptive and inferential statistics are two fundamental branches of statistical analysis, each serving distinct purposes. Descriptive statistics focus on summarizing and presenting data in a meaningful way. This involves calculating measures such as means, medians, and standard deviations, as well as creating visual representations like charts and graphs. These methods help to describe the basic features of the data set and provide a clear overview of its main characteristics.

On the other hand, inferential statistics go a step further by using sample data to make generalizations or predictions about a larger population. This branch involves techniques such as hypothesis testing, confidence intervals, and regression analysis. Inferential statistics allow researchers to draw conclusions and make decisions based on the data collected, even when it’s impractical to analyze an entire population. Together, these two branches provide a comprehensive toolkit for analyzing and interpreting data, from summarizing individual data points to making broader predictions and inferences.