Problem #2a:The following dummy variables were used to compute the multiple regressionequation to account for any seasonal effects in the data: Qrt1 = 1 if Quarter 1, 0otherwise; Qrt2 = 1 if Quarter 2, O otherwise; Qrt3 = 1 if Quarter 3, 0 otherwise.SUMMARY OUTPUTRegression StatisticsMultiple RR Square0.98970.9796Adjusted R Square0.9719Standard Error124.9667Observations12ANOVAdfSSMSSignificance FFRegressi on35996941.671998980.56128.000.00000042Residual8.124933.3315616.67Total116121875.00CoefficientsStandard Errort StatP-valueIntercept2491.6772.15034.530.0000000005Qtrl-711.67102.035-6.970.000115518Qtr2-1511.67102.035-14.820.00000042Qtr3326.67102.0353.200,012583566Using the above Excel output, compute the 4 quarterly forecasts for next year. Problem #2:The quarterly sales data (number of copies sold) for a college textbook over thepast three years follow.Quarter Year 1 Year 2 Year 311690180018502940900110026252900 29304250023602615

Given... dummy variables were used to compute the multiple regression equation to account for any…

Answered: Problem #2a: The following dummy…

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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Question 3. Calculate and interpret the regression line for the data.
Accountants at the GIll Co and Charted Brothers Accounting believed that several traveling executives were submitting unusually high travel vouchers upon returning from business trips. First, they took a sample of 200 vouchers submitted from the past year. Then they developed the following multiple-regression equation relating expected travel cost (Y) to a number of days on the road (X1) and distance traveled (X2) in miles: Y = 90.00 + 48.50X1 + 0.40X2 Here is additional information concerning the regression model: Sb1 = 0.038 Sb2 =0.019 R2 = 0.68 Se = 1.63 F-Statistic = 32.123 Durbin-Watson (d) statistic = 0.5436 What proportion of the total variation in expected travel cost is explained by the regression equation? Explain.
The datasetBody.xlsgives the percent of weight made up of body fat for 100 men as well as other variables such as Age, Weight (lb), Height (in), and circumference (cm) measurements for the Neck, Chest, Abdomen, Ankle, Biceps, and Wrist. We are interested in predicting body fat based on abdomen circumference. Find the equation of the regression line relating to body fat and abdomen circumference. Make a scatter-plot with a regression line. What body fat percent does the line predict for a person with an abdomen circumference of 110 cm? One of the men in the study had an abdomen circumference of 92.4 cm and a body fat of 22.5 percent. Find the residual that corresponds to this observation. Bodyfat Abdomen 32.3 115.6 22.5 92.4 22 86 12.3 85.2 20.5 95.6 22.6 100 28.7 103.1 21.3 89.6 29.9 110.3 21.3 100.5 29.9 100.5 20.4 98.9 16.9 90.3 14.7 83.3 10.8 73.7 26.7 94.9 11.3 86.7 18.1 87.5 8.8 82.8 11.8 83.3 11 83.6 14.9 87 31.9 108.5 17.3…
The image contains two graphs typical of the analysis of a simple linear regression model. It can be stated that: a. The variance of the errors seems constant b. The errors do not come from a normal distribution c. The linear model does not seem appropriate d. The residuals are close to the line and therefore there is normality in the data. Why? Thanks
Stoaches are fictional creatures that nest in truffula forests. A researcher wants to know whether there is a relationship between a stoach’s wingspan (?W, the predictor) and its nest height (?H, the response). A sample of 88 stoaches is observed, and for each, the wing-span (in cm) and the nest height (in m) are recorded. The observed data meet the assumptions for a linear regression, so the researcher fits the regression model and obtains a regression equation ℎ̂=−0.813+0.177?,h^=−0.813+0.177w, with standard error for the coefficient of ?w equal to 0.448. Determine the ?p-value from a test for a statistically significant linear dependence of nest height on wing-span. (Give your answer to 4 decimal places.
answer 6
Which of the multivariate regression parameters listed below would be best interpreted as: the proportion of variation in the dependent variable explain by all the independent variables in the model. a b1 X1 R2
A simple linear regression model was created to examine the relationship between the age of patients in years (i.e. the independent variable) and the patients' scores on a questionnaire that measures quality of life (i.e. the dependent variable). There were n=20 patients in the study, and some of the results of the regression are presented below: Estimated slope = -0.64 Standard error of the slope = 0.52 Estimated intercept = 42.0 Standard error of the intercept = 13.6 Based on these results, what would be the expected quality of life score for a patient who is 30 years old? Question 3 options: 61.2 22.8 1260.64 29.2

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