Question

please calculate the regressional model, the test hypothesis, the rejection region for the test statistic t, the test statistic t, and the percentage of total variation

Help A regional retailer would like to determine if the variation in average monthly store sales can, in part, be explained by the size of the store measured in square foot. A random sample of 21 stores was selected and the store size and average monthly sales were computed Complete parts a through c. Use a significance level of 0.10 where needed mm Click the icon to view the datatable between the store size and average monthly sales a. Compute the simple linear regression model using the sample data to determine whether variation in average monthly sales can be explained by store size. What is the linear regression model based on the sample data? 5-0.0 (Type Integers or decimals rounded to two decimal places as needed Data Table of Store Size and Monthly Sales - X Store Surse. FO 17360 15.820 17 500 17.480 15.790 20 290 15.250 16.900 11.820 12.00 15,510 12.580 21.590 14,010 16.790 14 990 18,510 18.410 16.750 Average Monthly Sales 5662.096.00 $535,683.00 5640,094.00 $575.785 00 5562.044.00 5601.137.00 $554 37400 5582.005.00 S47201000 5518.651 00 5618.650.00 546204600 5728 149.00 549768200 562631600 $500 640.00 5614 739 00 561493700 5687051 00 $713.798.00 $53764400 19.90 17 810 Priet Done

Answer 1

Solution:

We can use the excel regression data analysis tool to find the answer to the given questions. The excel steps are:

Enter the data in excel.

Click on Data > Data analysis > Regression > Ok

Input Y range: Select all the data under Average Monthly Sales including label

Input X range: Select all the data under Store size including label

Mark the labels

Choose the output range and the output is given below:

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.847545344
R Square	0.71833311
Adjusted R Square	0.703508537
Standard Error	4074446.609
Observations	21
ANOVA
	df	SS	MS	F	Significance F
Regression	1	8.04416E+14	8.04416E+14	48.45556793	1.2399E-06
Residual	19	3.15421E+14	1.66011E+13
Total	20	1.11984E+15
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	18131110.75	5954654.956	3.04486337	0.006664566	5667874.722	30594346.78
Store size	2474.982097	355.5496191	6.961003371	1.2399E-06	1730.808194	3219.156001

son tep A regional retailer would like to determine if the variation in average monthly store sales can, in part, be explained by the size of the store measured in square foot. A random sample of 21 stores was selected and the store size and average monthly sales were computed Complete parts a through c Use a significance level of 0.10 where needed Click the icon to view the datatable between the store size and average monthly sales a. Compute the simple linear regression model using the sample data to determine whether variation in average monthly sales can be explained by store size. What is the linear regression model based on the sample data? 9-0.0ű =18131110.75 + 2474.98(x) (Type integers or decimals rounded to two decimal places as needed)

interpret the slope coefficient Select the correct choice below and fill in the answer box to complete your choice (Type an integro decimal rounded to decimal laces 2474.98 CA Por each stolare foot of the average increase in monthly sales For each storal door of monthly sales, the average increase in stores sizes square feet Interpret the intercept coofficient. Select the correct choice below and in the answer box to complete your choice (Type an integrarea rounded to two decimal places and OA The warge month of a wore with square foot is OB. The size of a store with average only one is sure that c. A store with no force cannot occur, therefore, they interceptoes not have a meaning interpretation Dance of the slope coefficient of the regression model Ugrificance level of 0.06. What are the appropriate hypothes to tour?

Tout the cance of the slope coefficient of the regression model. Use a significance level of 0.06. What are the appropriate hypotheses to tout? M DAHA OBH 2.0 OCH 1-0 H 20 H-0 H 2.0 bo. H:8,20 OE H2,0 OR HOB, 50 HA, Determine the rejection region for the best statistiet Select the correct choice below and in any answer boxes to complete your choice (Type Integers decimal rounded to the decimal places as needed) ОА » OB.t-2.093 ort > 2.093 OC Calculate the simple linear regression des statistiet 6.961 type anger or decimal rounded to three decimal places as needed) falls Reject Since the last stic in the con region V the rol hypote Conclude that the reason moois griliant. This means that mowing is help in predicting