Descriptive and inferential statistics are the two main branches of statistics used to analyze data.

Descriptive statistics deals with summarizing, describing, and presenting data meaningfully. It includes methods for organizing, displaying, and summarizing data, such as measures of central tendency (mean, median, and mode), measures of dispersion (range, variance, and standard deviation), and graphical representations (histograms, box plots, and scatter plots). The goal of descriptive statistics is to provide a clear and concise summary of the data, which can help to understand the overall pattern and structure of the data.

Inferential statistics deals with drawing conclusions about a population based on a sample of data. It includes methods for estimation, hypothesis testing, and prediction. Estimation involves using sample statistics to make inferences about the population parameters. Hypothesis testing involves using sample data to test a claim about a population. And Prediction involves using a model to make predictions about future events or observations. The goal of inferential statistics is to use the information from a sample to make inferences or predictions about a population.

In summary, Descriptive statistics focuses on summarizing and describing the data, while Inferential statistics focus on drawing conclusions and making predictions about a population based on a sample of data.