Question

Online Store Monthly E-commerce Sales (in 1000 s) Online Advertising Dollars (1000 s) 1330 670 ||950 4.5 Il0.5 1560 |2.0 380 ||1.5 Note: this was a real data, but I changed some of the numbers to make your MANUAL computations easier. 1. Identify the most appropriate/logical Dependent and Independent variables for this study. 2. Is the linear relationship between the Dependent and Independent variables significant at a=0.05? Use both the global and individual tests to answer the questions. Show all your works. (3pts) 3. What are the Pearson correlation coefficient and Coefficient of determination? (0.5 pt) 4. Write the 95% confidence intervals for the regression coefficients (0.5 pt). Answer question 5 or 6, dependent on your answer to Question 1. (1 pt) 5. If you used the Sales as your dependent variable, then compute 95% confidence and prediction intervals for the Sales if we plan to spend $3,000 on advertisement. 6. If you used Advertising Dollar as your dependent variable, then compute 95% confidence and prediction intervals for Advertising Dollar, for the project sales of $700,000.

Answer 1

Studio File Edit Code View Plots Session O 1 1 -AA 1 Build Debug Profile Tools Help Go to file/function . Addins - Project: (None) source Environment History Connections A To Console To Source ) { Console Terminal x Jobs x test_ks_dbeta (x,4,7) > x=C(1.6,1.4,2.5,4.5,0.5,2.0,1.5) > y=C(360, 340,670,950,330,560,380) > plot(x,y) > d=data.frame(x,y) > rulm(y-x,d) > summary(r) ks.test(x,y="pbeta",4,7) x=C(1.6,1.4,2.5,4.5,0.5,2.0,1.5) y=C(360, 340,670,950,330,560,380) plot(x,y) d=data.frame (x,y) r=1m(y-x,d) summary(r) Call: Im(formula = y - x, data = d) Residuals: 2 3 -82.395 -67.164 69.065 4 -3.246 Files Plots ( 0) | Packages Zoom Help Viewer Export - 10 Publish - 16 81.376 12 143 -44.779 47.143 -44.779 Coefficients: Estimate Std. Error t value Pr (>1t|) (Intercept) 160.55 55.07 2.915 0.033190 * 176.16 23.797.406 0.000706 ** --- signif. codes: 0****' 0.001 "**' 0.01 '*' 0.05 ^,' 0.1''1 800 Residual standard error: 73.39 on 5 degrees of freedom Multiple R-squared: 0.9165, Adjusted R-squared: 0.8997 F-statistic: 54.85 on 1 and 5 DF, p-value: 0.0007065 400 600 # O Type here to search O De AⓇ A D 01) 10:46 04-03-2020

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» since re 0.9165 : correlation coefficient = JyZ - Jo.9163 = 0.9573 =257) € 95% confidance internal for CF) cſ = sec ex ttab) -(196.16 1 23.79% 2.59). ((oop) (23679+61.1402) = (175.16 1 61.1403) (115.0197,273.3603) lower confidence lintaset = 119.0 Uppe con bidal bound =273.3005 3