How do you calculate the mean, variance, and standard deviation of a dataset?

Calculating the mean, variance, and standard deviation of a dataset are fundamental statistical operations that provide valuable insights into the central tendency and variability of the data. Here's an in-depth explanation of how to calculate these statistics: 1. Mean (Average): The mean, often referred to as the average, represents the central tendency of a dataset. It's calculated by summing all the values in the dataset and then dividing by the total number of values. The formula for calculating the mean (\(\mu\)) of a dataset with "n" data points is: \[\mu = \frac{\sum_{i=1}^{n} x_i}{n}\] Where: - \(\mu\) is the mean. - \(x_i\) represents each individual data point. - The sum \(\sum_{i=1}^{n}\) means to add up all the data points from 1 to "n." 2. Variance: Variance measures the spread or dispersion of data points fro....