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?"
	Note that this sheet includes questions 10-16
	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
10)	Use Data > Data Analysis > Correlation to compute the correlation checking the Labels checkbox.
11)	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.
12)	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:
13)	a) Intercept =
	b) Slope =
	c) R2 =
	Perform Data > Data Analysis > Regression.
14)	Highlight the Y-intercept with yellow. Highlight the X variable in blue. Highlight the R Square in orange
15)	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.
16)	Is it appropriate to use this data to predict the amount of time that an 85-year-old will spend browsing online retailers ?
	If yes, what is the amount of time, if no, why?