Scatterplots

3 Concepts
Simple Linear Regression

5 Concepts
Analysis of Variance (ANOVA)

6 Concepts
Summary of Fit

3 Concepts
Parameter Estimates

1 Concept
Multiple LInear Regression (Leonard)

2 Concepts
Confidence Intervals (Part 2)

3 Concepts
Prediction Intervals

2 Concepts
The **Sum of Squares Total (SST) **sums all the squared-differences between the **observed** values and the **mean** of all values.

You may see it referred to as the "total" variance in the data points, as it includes both the "unexplained" variance (due to error) and the "explained" variance (from our regression model).

**Scenario**: Crammer Nation University wants to develop a regression equation to predict the "Number of Recruits" a given fraternity will receive this rush season given the "Parties Thrown" by the fraternity the previous year. They take a sample of 6 fraternities on campus, resulting in the following scatterplot with line of best fit.

**SST** = (-5)^{2} + (-1)^{2} + (-4)^{2} + (+3)^{2} + (+5)^{2} + (+2)^{2}**SST** = (25) + (1) + (16) + (9) + (25) + (4)**SST** = 80

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