Descriptive statistics are methods used to summarize and describe the main features of a dataset. They provide a useful starting point for analyzing data, as they can help to identify outliers, summarize key characteristics of the data, and inform the selection of appropriate statistical methods for further analysis. Descriptive statistics are broken down into measures of central tendency and measures of variability (spread). Measures of central tendency include the mean, median, and mode, while measures of variability include standard deviation, variance, minimum and maximum variables, kurtosis, and skewness. The primary objective of descriptive statistics is to effectively summarize and describe the main features of a dataset, providing an overview of the data and helping to identify patterns and relationships within it. Descriptive statistics are distinguished from inferential statistics by their aim to summarize a sample, rather than use the data to learn about the population that the sample of data is thought to represent. Descriptive statistics provide simple summaries about the sample and about the observations that have been made. Such summaries may be either quantitative, i.e. summary statistics, or visual, i.e. simple-to-understand graphs.