The manager of HelpME Senior Care is investigating why certain stores in York Region are performing better than others. She believes that 3 factors are related to any store's overall success (i.c., total sales revenue); the number of competing stores within a 14 km radius of each other, the population in the surrounding area within 30 km of any store and the amount any store spends on Google Adwords. She hires you to investigate this and provide some insight. A random sample of 39 stores is selected. For each store, the following information was gathered: y - total sales last year (in $000's) x1 = the number of competitors within a 14 km radius x2 = the population within the area (in 000's) x3 = the amount spent on Google Adwords (in $000's) The sample data produced the following results: SUMMARY OUTPUT Regression Statistics Multiple R 0.6986 R Square 0.4880 Adj R Square 0.4441 Standard Error 9.5618 Observations 39 ANOVA SS Regression 3 3.050.0000 Residual 35 3.200.0000 Total 6.250.0000 Regression output Coefficients Sid Error t Stat Intercept 8.4000 6 2000 1.3548 Competitors 1.6400 0.5800 2.8276 Population 21.5400 5.2000 4.1423 Adwords 0.7400 0.0800 9.2500 a. Is there enough evidence to conclude a relationship exists between population and sales? Assume a level of significance of 5%. b. State the population and sample regression line. c. Is the overall model valid? Assume a level of significance of 5%. d. If the variable 'AdWords' is removed, what will most likely happen to the Adj R37