Studies have shown that the frequency with which shoppers browse Internet retailers is related to the frequency with which they actually purchase products and/or services online. The following data show respondents age and answer to the question "How many minutes do you browse online retailers per year?"

Age (X)	Time (Y)
16	420
17	269
19	315
22	337
22	243
22	459
22	414
28	224
28	381
28	412
28	576
30	333
33	551
34	548
35	626
35	521
35	562
36	699
39	643
39	455
40	666
42	553
43	459
44	525
48	559
50	507
50	612
51	710
52	378
54	566
58	652
59	725
60	695
Use Data > Data Analysis > Correlation to compute the correlation checking the Labels checkbox.
Use the Excel function =CORREL to compute the correlation. If answers for #1 and 2 do not agree, there is an error.
The strength of the correlation motivates further examination.
a) Insert Scatter (X, Y) plot linked to the data on this sheet with Age on the horizontal (X) axis.
b) Add to your chart: the chart name, vertical axis label, and horizontal axis label.
c) Complete the chart by adding Trendline and checking boxes
Read directly from the chart:
a) Intercept =
b) Slope =
c) R2 =
Perform Data > Data Analysis > Regression.
Highlight the Y-intercept with yellow. Highlight the X variable in blue. Highlight the R Square in orange
Use Excel to predict the number of minutes spent by a 22-year old shopper. Enter = followed by the regression formula.
Enter the intercept and slope into the formula by clicking on the cells in the regression output with the results.
Is it appropriate to use this data to predict the amount of time that a 9-year-old will be on the Internet?
If yes, what is the amount of time, if no, why?