Inferential and Descriptive Stats: What’s the Difference?

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

Descriptive statistics is a branch of statistics used to summarize and describe the characteristics of a dataset. Descriptive statistics involves calculating summary measures, such as the mean, median, mode, range, standard deviation, variance, inter-quartile range (IQR) and using visualizations, such as histograms and scatterplots, to understand the distribution and patterns in the data. Descriptive statistics is concerned with describing the data and does not make any inferences or predictions about the population based on the sample data.


Inferential statistics is a branch of statistics used to make inferences or predictions about a population based on a sample of data. Inferential statistics involves using statistical tests, such as hypothesis tests and regression analysis, to determine whether there is a significant relationship or difference between the variables in the sample data and to make predictions about the population based on the sample data.

Summary

Descriptive statistics are used to summarize and describe the characteristics of a dataset. In contrast, inferential statistics are used to make predictions and inferences about the population based on a sample of data. Both types of statistics are essential tools in data analysis and are often used together to provide a complete picture of the data.


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