Statistical Tests
Statistical tests are a set of procedures used to make quantitative decisions about the likelihood of a hypothesis being true or false. In data science, statistical tests are used to determine whether there is a significant difference between two or more groups of data. These tests help to identify patterns and relationships in data, and to make predictions based on those patterns. There are many different types of statistical tests, including t-tests, ANOVA, chi-square tests, and regression analysis. Each test is designed to answer a specific question about the data, and the choice of test depends on the type of data being analyzed and the research question being asked. Statistical tests are an essential tool in data science, as they allow researchers to draw meaningful conclusions from their data and to make informed decisions based on those conclusions.
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