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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

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?

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