1. Based on the data available in the attached picture, Estimate the multivariate equation econometrically using excel.2. Interpret the results (coefficient, adjusted R square, p-values)3. Write the hypothesis for each independent variable. (null hypothesis and alternative hypothesis)4. Derive the elasticities for each variable using excel.● States.●●●●●●●●Estimate demand for soft drinks using a multiple regression programAlabamaArizonaArkansasCaliforniaColoradoSC200150237135121Connecticut 118Delaware217Florida242Georgia295Idaho85Illinois114SOFT DRINK DEMAND ESTIMATIONCans/Capita/YR 6Pack $Price2.191.991.932.592.292.491.992.291.892.392.35Income Temperature F13171125192728181416246662635652505272644652

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Answered: 1. Based on the data available in 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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Please help A researcher would like to predict the dependent variable YY from the two independent variables X1X1 and X2X2for a sample of N=18N=18 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test the significance of the overall regression model. Use a significance level α=0.05α=0.05. X1X1 X2X2 YY 58.4 17.9 58.1 50.9 45.7 56.9 57.3 44.7 53.4 36.3 38.7 61 57.4 28.4 63.8 36.5 34.8 51.8 65 29.3 59.7 64.2 50.8 60.2 70.1 25.2 63.4 49.2 60.6 53 70.8 26.1 73.8 30.7 80.2 51.4 54 28.3 53.5 36.7 53.5 44.2 35.4 48.5 36.6 42.8 43.2 41 52.7 56.1 54.7 43.8 52 51.3 SSreg=SSreg= SSres=SSres= R2=R2= F=F= P-value = What is your decision for the hypothesis test? Reject the null hypothesis, H0:β1=β2=0H0:β1=β2=0 Fail to reject H0H0 What is your final conclusion? The evidence supports the claim that one or more of the regression coefficients is non-zero The evidence supports the claim that all of…
27) A scatter plot shows no particular patterns between the two variables x and y. Given that the regression equation y= 4+5x and y=12.0 What is the best predicted value of y at x = 2? a 14 b 4 c 12 d 11
Which of the following refers to the variable that is being manipulated during an experiment? Constant Descriptive variable Dependent variable Independent variable
The DNP student is conducting data collection at the end of the implementation cycle in her DNP practice change project. The student also collected data before the intervention was implemented. The level of measurement is ratio and the student has parametric data. The student would like to measure the relationships between the pre-implementation and post-implementation samples. The student realizes she does NOT have a true independent variable. Using the interactive statistical flowchart, what statistical test will she conduct on his data? a. John's Relational test b. Palatium test c. Pearson's r d. Milli's test.
6) see pictures
1.) Create a scatterplot of the data. 2.) Find the equation of the regression line. 3.) Identify a characteristic of the data that is ignored by the regression line. a. The data has a pattern that is not a straight line b. There is no trend in the data c. There is an influential point that strongly affects the graph of the regression line d. There is no characteristic of the data that is ignored by the regression line.
+ Use a significance level of 0.05 where not specified. 1. The table gives the annual sales by salespersons with different years of experience in an auto dealership Years of Experience 2 5 7 8 92589 10 12 15 18 20 Sales Volume ($1000s) 80 97 110 120 130 160 180 200 220 A. Set up a table to calculate the regression analysis B. Develop a linear regression equation for the relationships. C. Calculate the residuals for each data point and find the mean residual. D. What would the expected sales volume for a salesperson with 16 years of experience. What would be the limits of prediction? 0
A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…
The accompanying data represent the weights of various domestic cars and their gas mileages in the city. The linear correlation coefficient between the weight of a car and its miles per gallon in the city is r= - 0.977. The least-squares regression line treating weight as the explanatory variable and miles per gallon as the response variable is -0.0061x +41.3297. Complete parts (a) and (b) below. V = Click the icon to view the data table. (a) What proportion of the variability in miles per gallon is explained by the relation between weight of the car and miles per gallon? The proportion of the variability in miles per gallon explained by the relation between weight of the car and miles per gallon is %. (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. % of the variance in is by the linear model. (Round to one decimal place as needed.) Data Table Full data set Miles per Miles per Weight (pounds), x Weight (pounds), x Car Car Gallon, y Gallon, y 1…
Which of the following refers to the variable that is being manipulated during an experiment? Constant Descriptive variable Dependent variable Independent variable
Please solve the last two parts. Part d and part e.
. A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below. Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 Family supportb . Enter a. Dependent Variable: Delinquency b. All requested variables entered. Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .249a .062 .062 1.59168 a. Predictors: (Constant), Family support ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 759.204 1 759.204 299.671 <.001b Residual 11479.107 4531 2.533 Total 12238.311 4532 a. Dependent Variable: Delinquency b. Predictors: (Constant), Family support…

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