Answered: The stepwise regression approach takes…

College Algebra

10th Edition

ISBN:9781337282291

Author:Ron Larson

Publisher:Ron Larson

Chapter3: Polynomial Functions

Section3.5: Mathematical Modeling And Variation

Problem 2ECP

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3.4 SKILL BUILDING EXERCISES Getting Regression Lines Only Find the equation of the regression line for the following data set. x 1 2 3 y 3 3 4
HOW DO YOU SEE IT? Discuss how well a linear model approximates the data shown in each scatter plot.
Cellular Phone Subscribers The table shows the numbers of cellular phone subscribers y in millions in the United States from 2008 through 2013. Source: CTIA- The Wireless Association Year200820092010201120122013Number,y270286296316326336 (a) Find the least squares regression line for the data. Let x represent the year, with x=8 corresponding to 2008. (b) Use the linear regression capabilities of a graphing utility to find a linear model for the data. How does this model compare with the model obtained in part a? (c) Use the linear model to create a table of estimated values for y. Compare the estimated values with the actual data.
Q3. A simple linear regression model can be used to mitigate a confounding. a. YesB. NoC. None of the above
A linear regression model has three features: x1, x2, x3. The t-stat value for each feature is -150, 110, -70, respectively. You want to build a simpler model by deleting one of the features, from your dataset. Which feature you can safely remove from the data? a. Cannot decide b. x3 c. x2 d. x1
IConsider the following multiple linear regression model and the Excel print out of its regression results: Beer = Bo + BIEDUC + B2AGE + BAGE? + BAGENDER + BERACE+ BEGENDER*RACE+ E, where Beer is monthly beer consumption (ounces), EDUC is years of education. We have 2 qualitative variables: gender and race. Gender takes 2 values, GEN=1 if the person is male and GEN=0 for females. The variable race also takes 2 values, RACE=1 if the person is white and RACE=0 if the person is not white. SUMMARY OUTPUT Regression Statistics R Square Adjusted R Square Standard Error Observations ??? 0.4684 ??? 40 ANOVA df MS Regression Residual ??? 319.3 64.8 ??? ??? ??? 8.43 Total ??? 597.5 Coefficients Standard Error Intercept -150.254 107.397 EDUC -16.7755 8.4579 75.45905 -1.72456 AGE 37.3261 AGE 0.5397 GEN 238.9424 81.6054 RACE 123.7404 103.1804 GEN. RACE 76.4308 51.0670 a. Calculate the missing numbers (???). b.Interpret the parameter of RACE (123.74). c. Is the parameter of RACE (Bs) significant?…
To determine if additional shelf space to the store brand canned vegetables or increasing advertising expenditures would be more effective strategy to expand sales would I use a simple linear model, multiple linear regression or an interaction model? What equation would I use
The hiring managers want to compare three different employment sources: Newspaper/Magazine, CareerBuilder, and Monster.com. Perform simple regressions as you did above predicting allocations for month 13 for those three employment sources. Which of the following statements would be the best conclusion from your analysis? Group of answer choices The model R-square for Monster.com is the highest R-square value of the three platforms. Therefore, management will likely provide the most funding for that platform, and we should focus on that above the other two. The models for Monster.com and Newspaper/Magazine are both significant, which means we should focus on these two platforms over CareerBuilder because management will likely provide us the most funding for those two platforms. The predicted monthly amount for CareerBuilder is lower than the predicted amount for Newspaper/Magazine. Therefore, they should expect the lowest amount of funding for CareerBuilder out of all of the…
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Develop an estimated multiple linear regression model that could be used to predict the alumni giving rate using the graduation, % of Classes Under 20, and Student/Faculty Ratio as independent variables. Discuss your findings. School SFR LT20 GT50 GRAD FRR GIVE Arizona State 24 42% 16% 59% 81% 8% Arkansas State—Jonesboro 19 49% 4% 37% 69% 11% Auburn 18 24% 17% 66% 87% 31% Air Force 8 74% 0.10% 81% 88% 11% Military Academy 8 95% 0% 86% 92% 28% Akron 20 39% 6% 35% 69% 15% Arizona 20 35% 17% 60% 79% 5% Arkansas 18 28% 18% 58% 83% 23% Ball State 18 34% 12% 57% 78% 11% Baylor 14 49% 9% 71% 85% 14% Boise State 21 33% 11% 27% 67% 8% Boston College 14 47% 6% 91% 96% 27% Bowling Green State 19 33% 7% 61% 75% 8% BYU 21 46% 12% 78% 84% 17% SUNY 16 36% 21% 67% 88% 9% Alabama 19 46% 16% 67% 85% 34% Central Michigan 22 32% 11% 54% 78% 8% Clemson 16 51% 13% 76% 91% 28% Colorado State 18 34% 19% 64% 83% 7% Berkley 17 62% 15% 91% 97% 12% Cincinnati…
Explain how a simple linear regression model could be used to examine whether a principle is reasonable
The residual plot for a linear regression model is shown below. Assess the fit of the linear model, and justify your answer. The line is a good fit because the points on the residual plot have a clear pattern. The line is a good fit because the points on the residual plot do not have any noticeable pattern. The line is not a good fit because the points on the residual plot do not have any noticeable pattern. The line is not a good fit because the points on the residual plot have a clear pattern.

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The stepwise regression approach takes into consideration all possible models. Group of answer choices True False