1 SUMMARY OUTPUT2Regression Statistics34 Multiple R5 R Square6 Adjusted R Square7 Standard Error8 Observations910 ANOVA1112 Regression13 Residual14 Total151617 Intercept18 Math Score (X)0.693052530.4803218090.30709574510.44664636df5SSMSF1 302.6027397 302.6027397 2.7728033327.3972603 109.13242014630Significance F0.19446749Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%26.78082192 30.51824016 0.877534936 0.444799 -70.34183872 123.9034826 -70.34183872 123.90348260.643835616 0.386647728 1.665173669 0.194467 -0.586650018 1.874321251 -0.586650018 1.874321251 Read and analyze the result above using theSimple Linear Regression.Question: What is the equation of the linearregression?OY=26.78 +0.64XOY=0.88 +1.67XY = 0.64 +26.78XO Y = 1.67 +0.88X

here given , summary Output of Regression Analysis y - Intercept = 26.78082192 Coefficient of…

Answered: Question: What is the equation of the…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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8 The sales of 14 store branches and display area(in square feet) were obtained. The objective is to predict sales in terms of area of dispslay. Data were encoded into MS Excel. Output is shown below. REGRESSION STATISTICS Multiple R 0.954 R Square 0.910 Adjusted R square 0.902 Standard Error 936.85 Observations 14 Coefficients Standard t stat Error Intercept 901.25 513.02 1.76 Size 1.69 0.15 11.00 Question: Predict the sales if the display area utilized for a month is 3,000 square feet. Group of answer choices A. P5,971.25 B. P33,001.76 C. P2,703,751.69
8 The sales of 14 store branches and display area(in square feet) were obtained. The objective is to predict sales in terms of area of dispslay. Data were encoded into MS Excel. Output is shown below. REGRESSION STATISTICS Multiple R 0.954 R Square 0.910 Adjusted R square 0.902 Standard Error 936.85 Observations 14 Coefficients Standard t stat Error Intercept 901.25 513.02 1.76 Size 1.69 0.15 11.0 Predict the sales if the display area utilized for a month is 3,000 square feet. Group of answer choices A.P5,971.25 B. P33,001.76 C. P2,703,751.69
Lyme disease is an inflammatory disease that results in a skin rash and flulike symptoms. It is transmitted through the bite of an infected deer tick. The following data represent the number of reported cases of Lyme disease and the number of drowning deaths for a rural county. Cases_of_Lyme_Disease Drowning_Deaths Month3 0 J2 1 F2 2 M4 1 A5 3 M15 9 J22 17 J13 5 A6 3…
A sales manager for an advertising agency believes there is a relationship between the number of contacts that a salesperson makes and the amount of sales dollars earned. A regression ANOVA shows the following results:ANOVA df SS MS F Significance F Regression 1.00 13,555.42 13,555.42 156.38 0.00 Residual 8.00 693.48 86.88 Total 9.00 14,248.90 What is the value of the standard error of estimate? Multiple Choice 9.321 8.789 8.339 86.88
0.6.3 Question 3 Is the cubic effect significant? How about quadratic and linear effects? Analysis of Variance Table Response: EX Df Sum Sq Mean Sq F value Pr(>F) MET 1 332 332 0.1246 0.7257742 I(MET^2) 1 37504 37504 14.0572 0.0005141 *** I(MET^3) 1 7245 7245 2.7154 0.1065086 Residuals 44 117390 2668 > anova(quadModel) Analysis of Variance Table Response: EX Df Sum Sq Mean Sq F value Pr(>F) MET 1 332 332 0.120 0.7306134 I(MET^2) 1 37504 37504 13.541 0.0006216 *** Residuals 45 124635 2770 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Refer to the ANOVA table for this regression. Source d.f. SS MS Regression 3 1,196,410 398,803 Error 26 379,332 14,590 Total 29 1,575,742 (a) State the degrees of freedom for the F test for overall significance. (c-1) Calculate the F statistic. (d) Calculate R2 and R2adj.
9. This small dataset reports the Average Class Size, Combined SAT score, and the pct of the class that Attends 4 Year Colleges. Estimate a regression to answer the following. Each additional student's increase in avg class size is associated with a _____________ increase in SAT scores. Round your answer to two decimal places. District AverageClass Size CombinedSAT Score % Attend4-Year College Blue Springs, MO 25 1083 74 Garden City, NY 18 997 77 Indianapolis, IN 30 716 40 Newport Beach, CA 26 977 51 Novi, MI 20 980 53 Piedmont, CA 28 1042 75 Pittsburg, PA 21 983 66 Scarsdale, NY 20 1110 87 Wayne, PA 22 1040 85 Weston, MA 21 1031 89 Farmingdale, NY 22 947 81 Mamaroneck, NY 20 1000 69 Mayfield, OH 24 1003 48 Morristown, NJ 22 972 64 New Rochellle, NY 23 1039 55 Newtown Square, PA 17 963 79 Omaha, NE 23 1059 81 Shaker Heights, OH 23 940 82
Which of the following is true about local control? I. It employs the necessary practices or techniques to remove or minimize the effect of extraneous factors on the response of the experimental units. II. It involves the repetition of the basic experiment to provide a valid estimate of the experimental error.
Motorcycle Accidents. The Scottish Executive, Analytical Services Division Transport Statistics, compiles information on motorcycle accidents in Scotland. During one year, data on the number of motorcycle accidents, by day of the week and type of road (built-up or non–built-up), are as presented on the WeissStats site. a. Group the bivariate data for these two variables into a contingency table. b. Determine the conditional distribution of day of the week within each type-of-road category and the marginal distribution of day of the week. c. Determine the conditional distribution of type of road within each day of the week and the marginal distribution of type of road. d. Does an association exist between the variables “day of the week” and “type of road” for these motorcycle accidents? Explain your answer.
Refer to the ANOVA table for this regression. Source d.f. SS MS Regression 2 578,850 289,425 Error 21 378,420 18,020 Total 23 957,270 Using Appendix F on the pictures, calculate F.05, a=0.05, F statistics, R2, and R2 adj.
Month No. of Advertisements Amt of sales 1 20 61000 2 24 77000 3 30 72000 4 23 66000 5 27 85000 6 25 77000 7 32 90000 8 35 10000 9 21 63000 10 34 97000 11 26 83000 12 29 70000 a) show above data on a scatter plot and include regression line. b) calculate the regression equation and a r-squared c) construct a 95% confidence interval for question b.
17. The following results are from data where the dependent variable is the selling price of used cars, the independent variables are similar to those in the above regression along with some additional variables. The data were split into 2 samples and the following regression results were obtained from the split data. SUMMARY OUTPUT Regression Statistics Multiple R 0.846 R Square 0.715 Adjusted R Square 0.653 Standard Error 872.9 Observations 49 ANOVA df SS MS F Significance F Regression 9 76575468 8508385 11.2 1.03933E-08 Residual 40 30479336 761983 Total 49 107054804 Coefficients Standard Error t Stat P-value Intercept…

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Question: What is the equation of the linear regression?