74. Abby Kratz, a market specialist at the market research firm of Saez, Sikes, and Spitz, isanalyzing household budget data collected by her firm. Abby's dependent variable is monthlyhousehold expenditures on groceries (in $'s), and her independent variable is annual householdincome (in $1,000's). Regression analysis of the data yielded the following tables.InterceptXSourceRegressionResidualTotalCoefficients39.149421.792312Standard Error22.301820.407507t Statistic p-value1.755436 0.1097124.398234 0.001339dfSSMS1 16850.99 16850.99 19.344469 7839.915 871.101710 24690.91Se = 29.51443r2 = 0.682478For a household with $50,000 annual income, Abby's model predicts monthly groceryexpenditures of

The annual household income is the independent variable .The monthly expenditure on groceries is the…

Answered: 74. Abby Kratz, a market specialist at…

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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Body Fat. Where we considered the regression of percentage of body fat on nine body measurements: height, weight, hip, forearm, neck, wrist, triceps, scapula, and sup. Describe and discuss problems that could have arisen in the collection of the data for this regression analysis.
The following data gives the number of employees at the bookstore and the number of minutes students wait in line to buy books at the beginning of the term. The independent variable is the number of employees and the dependent variable is the number of minutes. What is the y intercept? SSxx = 56.857; SS=2095.714; SSxy=-322.571 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square XA356899 0.96 0.93 0.91 y 67 54 47 33 31 25 12
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Use the Financial database from “Excel Databases.xls” on Blackboard. Use Total Revenues, Total Assets, Return on Equity, Earnings Per Share, Average Yield, and Dividends Per Share to predict the average P/E ratio for a company. Use Excel to develop the multiple linear regression model. Assume a 5% level of significance. Which independent variable is the strongest predictor of the average P/E ratio of a company? A. Total Revenues B. Average Yield C. Earnings Per Share D.Return on Equity E. Total Assets F.Dividends Per Share Company Type Total Revenues Total Assets Return on Equity Earnings per Share Average Yield Dividends per Share Average P/E Ratio AFLAC 6 7251 29454 17.1 2.08 0.9 0.22 11.5 Albertson's 4 14690 5219 21.4 2.08 1.6 0.63 19 Allstate 6 20106 80918 20.1 3.56 1 0.36 10.6 Amerada Hess 7 8340 7935 0.2 0.08 1.1 0.6 698.3 American General 6 3362 80620 7.1 2.19 3 1.4 21.2 American Stores 4 19139 8536 12.2 1.01 1.4 0.34 23.5 Amoco 7 36287…
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Which of the following statements best describes linear regression? A measure of the degree of dependence between two variables. A statistical technique using pairs of data and identifying a line which ‘best fits’ all of the pairs of observations. A measure of the proportion of changes in the dependent variable which can be explained by a change in the independent variable. Shows individual costs against their associated activity levels but makes no attempt to identify a linear relationship between them.
The correct answer is option C but I do not know how to find the number that go inside it.
What is the explanatory variable, what is the response variable. What is the regression equation for this data. Plot the regression line in your calculator and draw it on your graph. Interpret in context the slope. Interpret in context the y-intercept. What is the residual at 45 years of age. Plot the residual plot on the axis to the right

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