12.3.5.1 - Example: Quiz and exam scores

Data from a sample of 50 students were used to build a regression model using quiz averages to predict final exam scores. Construct a 95% confidence interval for the slope.

This example uses the Minitab file: Exam.mpx

We can use the coefficients table that we produced in the previous regression example using the exam data.

Coefficients
Term Coef SE Coef T-Value P-Value VIF
Constant 12.1 11.9 1.01 0.315  
Quiz_Average 0.751 0.141 5.31 0.000 1.00

The general form of a confidence interval is sample statistic \(\pm\) multiplier(standard error).

We have the following:

  • \(b_1\) (sample slope) is 0.751
  • t multiplier for degrees of freedom of (50-2) = 48 is 2.01
  • The standard error of the slope (\(SE_{b_1}\) is 0.141 from our table

The confidence interval is...

\begin{align} \text{sample statistic} &\pm \text{multiplier*standard error}\\ 0.751 &\pm 2.01 (0.141)\\ 0.751&\pm 0.283 \\ [0.468 &, 1.034] \end{align}

Interpret

I am 95% confident that the slope for this model is between 0.468 and 1.034 in the population.