Question

This following data is for Wray Enterprises. We have tracked the amount of money they spend on advertising and the sales volume for their product.

Month	Advertising	Sales
1	1000	5200
2	1500	6000
3	1900	7200
4	1400	5400
5	2200	6500
6	2468	7600
7	1210	6200
8	1698	6000
9	2234	7500

Suppose you perform the test to determine if there is a relationship between advertising and sales and the value of the test statistic is 4.5949 and find (p-value < .01). Here is the MS Excel output:

	Coefficients	Standard Error	t Stat	P-value
Intercept	3784.3928
advertising	1.5080	0.3282	4.5949	0.0025

Would you use a model based on this data to predict the sales for a month with $500 dollars of advertising?  $1500 dollars of advertising? $2400 dollars of advertising?

A.) I would use the model to predict for advertising of $500 only.

B.) I would use the model to predict for advertising of $2400 only.

C.) I would use the model to predict for advertising of $1500 and $2400 only.

D.) I would use the model to predict for any level of advertising because there is sufficient evidence of a relationship between advertising and sales.

E.) I would not use the model to predict for any level of advertising because there is sufficient evidence of a relationship between advertising and sales

Answer 1

Using the MS excel output data table

we can see that the p value corresponding to the independent variable advertising is 0.0025, which is less than 0.01 level of significance. This means we can conclude that there is a significant relationship between dependent variable sales and independent variable advertising.

We can use the model for predicting sales based on any value of advertising as the relationship is significant

therefore, option D is correct