Descriptive statistics is a branch of statistics that involves the collection, analysis, and presentation of data in a way that summarizes and describes its main features. It provides a set of tools and techniques to summarize and describe the characteristics of a dataset, such as its central tendency, variability, distribution, and shape.
Some common measures of central tendency include the mean, median, and mode, which provide information about the average or typical value of a dataset. Measures of variability, such as range, variance, and standard deviation, provide information about the spread or dispersion of the data around its central tendency. Other descriptive statistics, such as quartiles, percentiles, and skewness, provide information about the distribution and shape of the data.
Descriptive statistics can be used to summarize both numerical and categorical data. For numerical data, descriptive statistics can be used to summarize continuous or discrete variables, such as height, weight, age, income, or test scores. For categorical data, descriptive statistics can be used to summarize the frequencies or proportions of different categories, such as gender, race, or educational level.
Descriptive statistics can be used to provide insights into the characteristics of a dataset, to compare different datasets, to identify outliers or unusual observations, to detect patterns or trends in the data, and to make data-driven decisions. They are widely used in various fields, including business, economics, social sciences, health sciences, and engineering, among others.