This is simple question from hypothesis testing You are required to;a. Complete the missing entries from A to L in this outputANSWER:b. Derive the regression modelANSWER:c. What does the standard error of estimate tell you about the model?ANSWER:d. Assess the independent variables significance at 5% level (develop hypothesis if necessary inthe analysis)?ANSWER: Yummy Lunch Restaurant needs to decide the most profitable location for their business expansion.Marketing manager plans to use a multiple regression model to achieve their target. His modelconsiders yearly revenue as the dependent variable. He found that number of people within 2KM(People), Mean household income(income), no of competitors and price as explanatory variables ofcompany yearly revenue.The following is the descriptive statistics and regression output from Excel.RevenuePeopleIncomeCompetitorsPrice343985.685307.898635970.28139.084528141522.082.80.142857Mean5.88Standard Error582.137838541339.50.051030203Median345186.5803235.75#N/A5917ModeStandard DeviationSample Variance#N/A3983.47613967225.298437532.511154118.3347181.0101530.3808380270.130204082284140868939316944211.511.020408Sum171982842985132076148140Count5050505050SUMMARYOUTPUTRegression Statistics0.77Multiple RR SquareAdjusted R SquareStandard ErrorAB25139.79Observations50.00ANOVASignificanceofMSF40585378295RegressionResidualTotalH3.0831E-0828440403984GE69025780279t Stat-0.8706P-value0.38860.08910.00000.08570.1251CoefficientsStandard Error78524.72513.70510.93583818.5426-88363.1524InterceptPeople8.43947.2723-6709.4320IncomeCompetitorsPriceK12ivate Wind15988.704810219.0263LGo to Settings to

as per our company guidelines we are supposed to answer ?️only first 3 sub-parts. Kindly repost…

company yearly revenue. The following is the descriptive statistics and regression output from Excel. Revenue Реople Income Competitors Price Mean Standard Error Median 5970.26 5.68 0.142857 0.051030203 5.75 343985.88 2.8 41522.08 582.1378385 41339.5 #N/A 5307.89863 139.0845281 8032 345186.5 3 Mode 3 #NIA 37532.51115 1408689393 5917 Standard Deviation Sample Variance 983.47813 4118.334718 16944211.51 2078148 1.010153 0.380838027 987225.2984 1.020408 0.130204082 Sum 17198284 298513 140 284 Count 50 50 50 50 50 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error 0.77 A B 25139.79 50.00 Observations ANOVA Significance F. 3.0831E-08 of MS F Regression C 40585376295 28440403984 Residual G Total E 69025780279 Coefficients Standard Error -68363.1524 t Stat -0.8708 0.3886 P-value 1524 76524.7251 Intercept Реople Income Competitors Price | 0.0801 J 0.0000 K 0.0857 L 0.1251 8.4394 3.7051 0.9358 3818.5426 10219.0283 7.2723 -6709.4320 2tivate Winc 15968.7848

company yearly revenue. The following is the descriptive statistics and regression output from Excel. Revenue Реople Income Competitors Price Mean Standard Error Median 5970.26 5.68 0.142857 0.051030203 5.75 343985.88 2.8 41522.08 582.1378385 41339.5 #N/A 5307.89863 139.0845281 8032 345186.5 3 Mode 3 #NIA 37532.51115 1408689393 5917 Standard Deviation Sample Variance 983.47813 4118.334718 16944211.51 2078148 1.010153 0.380838027 987225.2984 1.020408 0.130204082 Sum 17198284 298513 140 284 Count 50 50 50 50 50 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error 0.77 A B 25139.79 50.00 Observations ANOVA Significance F. 3.0831E-08 of MS F Regression C 40585376295 28440403984 Residual G Total E 69025780279 Coefficients Standard Error -68363.1524 t Stat -0.8708 0.3886 P-value 1524 76524.7251 Intercept Реople Income Competitors Price | 0.0801 J 0.0000 K 0.0857 L 0.1251 8.4394 3.7051 0.9358 3818.5426 10219.0283 7.2723 -6709.4320 2tivate Winc 15968.7848

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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Concept explainers

Confidence Intervals

When we calculate intervals in probability and statistics, it can be simply termed as finding out a confidence interval. The confidence interval is usually calculated from the data set which is observed. The value of the parameter that needs to be calculated is present here only.

Question

This is simple question from hypothesis testing

You are required to;
a. Complete the missing entries from A to L in this output
ANSWER:
b. Derive the regression model
ANSWER:
c. What does the standard error of estimate tell you about the model?
ANSWER:
d. Assess the independent variables significance at 5% level (develop hypothesis if necessary in
the analysis)?
ANSWER:

Yummy Lunch Restaurant needs to decide the most profitable location for their business expansion.
Marketing manager plans to use a multiple regression model to achieve their target. His model
considers yearly revenue as the dependent variable. He found that number of people within 2KM
(People), Mean household income(income), no of competitors and price as explanatory variables of
company yearly revenue.
The following is the descriptive statistics and regression output from Excel.
Revenue
People
Income
Competitors
Price
343985.68
5307.89863
5970.28
139.0845281
41522.08
2.8
0.142857
Mean
5.88
Standard Error
582.1378385
41339.5
0.051030203
Median
345186.5
8032
3
5.75
#N/A
5917
Mode
Standard Deviation
Sample Variance
#N/A
3
983.47613
967225.2984
37532.51115
4118.334718
1.010153
0.380838027
0.130204082
284
1408689393
16944211.51
1.020408
Sum
17198284
298513
2076148
140
Count
50
50
50
50
50
SUMMARY
OUTPUT
Regression Statistics
0.77
Multiple R
R Square
Adjusted R Square
Standard Error
A
B
25139.79
Observations
50.00
ANOVA
Significance
of
MS
F
40585378295
Regression
Residual
Total
H
3.0831E-08
28440403984
G
E
69025780279
t Stat
-0.8706
P-value
0.3886
0.0891
0.0000
0.0857
0.1251
Coefficients
Standard Error
78524.7251
3.7051
0.9358
3818.5426
-88363.1524
Intercept
People
8.4394
7.2723
-6709.4320
Income
Competitors
Price
K
12ivate Wind
15988.7048
10219.0263
L
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