Statistics

1. What was the average effect of the process change? Did the process average increase or decrease and by
   how much?
   Calculate the average for each process and compare if the average increased or decreased, and by how
   much.
2. Analyze the data using the regression model y = b0 + b1x, where y = time to approve and mail a claim
   (weekly average), x = 0 for the old process, and x = 1 for the new process.
   Use Excel to calculate the Regression line for the model. Then, analyze the slope (b1) and the y-intercept (b0)
   For example: Is there a negative or positive association based on the linear regression? What element of the
   linear regression determine that association?
3. How does this model measure the effect of the process change?
   To answer this question, perform a data analysis of each model using Excel, compare the coefficient of
   determination (r2 ), and explain the meaning of the value. Express your coefficient of determination in
   percentage. Remember to add here the Excel data analysis chart.
4. How much did the process performance change on the average? (Hint: Compare the values of b1 and the
   average of new process performance minus the average of the performance of the old process.)

Sample Solution