Descriptive statistics is the branch of statistics that summarizes and describes data, while inferential statistics is used to make inferences or predictions about a population based on a sample. Descriptive statistics aims to provide a snapshot of the data and its characteristics, while inferential statistics goes beyond the data and attempts to draw conclusions about a larger population.
Descriptive statistics involves summarizing and describing the main features of a dataset, such as measures of central tendency (mean, median), variability (standard deviation), and visual representations (graphs, charts). Inferential statistics, on the other hand, involves making predictions or generalizations about a population based on a sample, using probability theory and hypothesis testing.
Inferential statistics involves using sample data to make inferences or draw conclusions about a larger population. It aims to make predictions and generalizations based on the sample data. On the other hand, descriptive statistics focuses on summarizing and organizing the characteristics of a data set, providing a clear and concise overview without any inference or speculation about the population.
