185. Simple Linear Regression
- : dependent variable
- : independent variables
- : intercept (value of when )
- : slope (change in for a one-unit change in )
- : error term (difference between the actual data points and the predicted values)
Example
Data
| (Hours Studied) | (Test Score) |
|---|---|
| 1 | 2 |
| 2 | 3 |
| 3 | 5 |
| 4 | 4 |
| 5 | 6 |
Step 1: Calculate Means
Step 2: Calculating Slope
- The numerator
- The denominator
- The slope is
Step 3: Calculate Intercept
Step 4: Calculate p-Value
- Calculate Standard Error of the Slope ()
- Calculate the Residual Sum of Squares (RSS)
- Calculate the t-statistic for the Slope
- Determine Degrees of Freedom
- Look up the p-value corresponding to with 3 degrees of freedom
Step 5: Calculate ()
(Regression Sum of Squares): sum of the squared differences between the predicted values and the mean of the observed values.
(Total Sum of Squares): sum of the squared differences between the observed values and the mean of the observed values.
Adjusting for the number of independent variables
- : number of observations
- : number of independent variables