Stats Midterm Survival Kit: Descriptive to Inferential
Most students fail statistics not because they can't do the math, but because they treat it like a math class instead of a logic class. This guide focuses on the 'why' behind the formulas.
Before you dive into the practice exam, remember: The data is trying to tell a story. Your job is to make sure you aren't misinterpreting the plot.
1. Describing Data (Without Lying) #
The goal of descriptive stats is to reduce a massive dataset into a digestible summary. But every summary loses information.
The Variance Trap: Why do we divide by for samples but for populations? It's called Bessel's Correction. Using would consistently underestimate the true population variance.
- Sample Variance:
- Standard Deviation:
Pro Tip: If your distribution is skewed, the Mean is a liar. Use the Median and IQR (Interquartile Range) to describe 'typical' values in datasets with heavy outliers (like house prices or salaries).