In today’s blog I would mainly talk about the topics which is related to the uncovering the data interpretations for the police shooting in the different states of the United States based on the variables in the datasets such as  T-Test, analysis of the variance (ANOVA), and Bayes’ Theorem.

t-test – The means of two groups are compared using a t-test, a statistical hypothesis test, to see if there is a significant difference between them. It’s a widely used technique in data analysis to determine the likelihood that observed differences between two groups are real or may have happened by accident. The most common t-test is an independent samples t-test and the method for that used in the analysis is the Null Hypothesis (H0) and Alternative Hypothesis (H1).

ANOVA – The statistical method known as Analysis of Variance, or ANOVA, compares the means of three or more groups to see if there are any statistically significant differences between them. It expands the use of the t-test, which compares means between two groups, to scenarios involving several groups. When attempting to determine whether many treatment groups or factors differ significantly from one another, ANOVA is a particularly helpful tool.

Bayes’ Theorem – A cornerstone of probability theory and statistics is the Bayes’ Theorem, which bears the name of the 18th-century mathematician and theologian Thomas Bayes. It is commonly used to update and modify the probability of a hypothesis or occurrence depending on fresh data or information in data analysis, machine learning, and many other domains. A framework for reasoning under uncertainty and drawing probabilistic conclusions is provided by Bayes’ Theorem.