A researcher uses a regression equation to predict home heatingbills (dollar cost), based on home size (square feet). The correlationbetween predicted bills and home size is 0.70. What is the correctinterpretation of this finding?(A) 70% of the variability in home heating bills can be explained byhome size.(B) 49% of the variability in home heating bills can be explained byhome size.(C) For each added square foot of home size, heating billsincreased by 70 cents.(D) For each added square foot of home size, heating billsincreased by 49 cents.(E) None of the above.

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Answered: A researcher uses a regression equation…

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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Develop an estimated multiple regression equation that relates risk of a stroke to a person's age, systolic blood pressure and whether the person is a smoker. x1=persons age x2systrolic blood pressure x3=whether person is a smoker or non smoker
A linear model fit to predict weekly Sales of frozen pizza (in kilograms) from the average Price (in dollars per unit) charged by a sample of stores in 41 recent weeks is Sales = 141,870.25-24,445.32 Price. For the data used to create the model, the average Sales was 52,750 kilograms (SD = 10,282 kilograms) and the correlation between Price and Sales was r=-0.554. If the Price in a particular week was 2 SD higher than the mean Price, how much pizza would the model predict was sold that week? The model would predict that kilograms of frozen pizza were sold. (Round to the nearest integer as needed.)
Based on the analyst's data and regression line, complete the following. For these data, values for earnings per share that are greater than the mean of the values for earnings per share tend to be paired with current stock prices that are (greater than, lesser than) the mean of the current stock prices. According to the regression equation, for an increase of one dollar in earnings per share, there is a corresponding increase of how many dollars in current stock price?
You estimate a regression equation that estimates individuals’ yearly income as a function of age (measured in years), years of education, and their score on a standardized intelligence exam (IQ test). The estimated coefficients are: I = 26.3 + 4.21*Age + 7.21*Education + .23 * IQ Where I is income measured in thousands of dollars. Based on the regression results, how much more should an individual earn after attending graduate school for two years? Explain your reasoning.
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The owner of Showtime Movie Theatres Inc. would like to predict weekly gross revenue as a function of advertising expenditures. Use 0.05 level of significance.Historical data for a sample of eight weeks follow: Weekly Gross Renvenue Telelvision Newspaper Adveritising ($1000s) Adveritising a) Develop an estimated regression equation to predict weekly gross revenue as a function of advertising expenditures. ($1000s) ($1000s) 96 5.0 1.5 90 20 2.0 b) Explain in simg when 1000s are spent on television and newspaper then the revenue will in 95 4.0 1.5 92 2.5 2.5 c) Predict weekly 95 3.0 3,3 94 3.5 2.3 d) What is the R2 value? 0.9190 94 2.5 4.2 94 3.0 2.5 e) What is the Hypothesis Test? Use the t test to determine the significance of each independent variable. State the t test, p-values, and your conclusion. g) What is the cor Reject Ho SUMMARY OUTPUT pression Statstica Mutiple R 0.958663444 0.9190356 R Square 0.88664984 Adusted R Square Standard Eror 0.642587303 Obervations ANOVA Syaicance…
Illustrate the regression equation?
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Researchers are interested in predicting the height of a child based on the heights of their mother and father. Data were collected, which included height of the child ( height), height of the mother ( mothersheight ), and height of the father (fathersheight ). The initial analysis used the heights of the parents to predict the height of the child (all units are inches). The results of the analysis, a multiple regression, are presented below. . regress height mothersheight fathersheight Source Model Residual Total height mothersheight fathersheight _cons SS 208.008457 314.295372 522.303829 df 2 104.004228 8.49446952 37 MS 39 13.3924059 Coef. Std. Err. .6579529 .1474763 .2003584 .1382237 9.804327 12.39987 t P>|t| 4.46 0.000 C 0.156 0.79 0.434 Number of obs = F( 2, 37) = Prob > F R-squared Adj R-squared = Root MSE = = .3591375 -.0797093 -15.32021 = 40 12.24 0.0001 0.3983 0.3657 2.9145 [95% Conf. Interval] .9567683 .4804261 34.92886 What are the null and alternative hypotheses…
A patient is classified as having gestational diabetes if their average glucose level is above 140 milligrams per deciliter (mg/dl) one hour after a sugary drink is ingested. Rebecca's doctor is concerned that she may suffer from gestational diabetes. There is variation both in the actual glucose level and in the blood test that measures the level. Rebecca's measured glucose level one hour after ingesting the sugary drink varies according to the Normal distribution with μ=140+5 mg/dl and σ=5+1 mg/dl. Using the Central Limit Theorem, determine the probability of Rebecca being diagnosed with gestational diabetes if her glucose level is measured: Once? n=5+2 times n=5+4 times Comment on the relationship between the probabilities observed in (a), (b), and (c). Explain, using concepts from lecture why this occurs and what it means in context.

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