3.4.3.1 - Minitab: SLR

Minitab 18

Minitab®  – Simple Linear Regression

We previously created a scatterplot of quiz averages and final exam scores and observed a linear relationship. Here, we will use quiz scores to predict final exam scores.

  1. Open the Minitab file: Exam.mwx (or Exam.csv)
  2. Select Stat > Regression > Regression > Fit Regression Model...
  3. Double click Final in the box on the left to insert it into the Responses (Y) box on the right
  4. Double click Quiz_Average in the box on the left to insert it into the Continuous Predictors (X) box on the right
  5. Click OK

This should result in the following output:

Regression Equation

Final = 12.1 + 0.751 Quiz_Average

Coefficients

Term Coef SE Coef T-Value P-Value VIF
Constant 12.1 11.9 1.01 0.3153  
Quiz_Average 0.751 0.141 5.31 0.000 1.00

Model Summary

S R-sq R-sq(adj) R-sq(pred)
9.71152 37.04% 35.73% 29.82%

Analysis of Variance

Source DF Adj SS Adj MS F-Value P-Value
Regression 1 2664 2663.66 28.24 0.000
Quiz_Average 1 2664 2663.66 28.24 0.000
Error 48 4527 94.31    
Total 49 7191      

Fits and Diagnostics for Unusual Observations

Obs Final Fit Resid Std Resid  
11 49.00 70.50 -21.50 -2.25 R
40 80.00 61.22 18.78 2.03 R
47 37.00 59.51 -22.51 -2.46 R

R Large residual

Interpretation

In the output in the above example we are given a simple linear regression model of Final = 12.1 + 0.751 Quiz_Average

This means that the y-intercept is 12.1 and the slope is 0.751.