Observations are taken on sales of a certain mountain bike in 25 sporting goods stores. The regression model was Y= total sales (thousands of dollars), X1 = display floor space (square meters), X2 = competitors' advertising expenditures (thousands of dollars), X3 = advertised price (dollars per unit). (a) Fill in the values in the table given here. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your t-values to 3 decimal places and p-values to 4 decimal places.) Coefficient Predictor Intercept FloorSpace Competing Ads Price p-value SE 351.9 1.74 tcalc 1,219.0 11.002 -6.021 3.932 -0.14944 0.08582 (b-1) What is the critical value of Student's tin Appendix D for a two-tailed test at a = .01? (Round your answer to 3 decimal places.) t-value =

Observations are taken on sales of a certain mountain bike in 25 sporting goods stores. The regression model was Y= total sales (thousands of dollars), X1 = display floor space (square meters), X2 = competitors' advertising expenditures (thousands of dollars), X3 = advertised price (dollars per unit). (a) Fill in the values in the table given here. (Negative values should be indicated by a minus sign. Leave no cells blank - be certain to enter "0" wherever required. Round your t-values to 3 decimal places and p-values to 4 decimal places.) Coefficient Predictor Intercept FloorSpace Competing Ads Price p-value SE 351.9 1.74 tcalc 1,219.0 11.002 -6.021 3.932 -0.14944 0.08582 (b-1) What is the critical value of Student's tin Appendix D for a two-tailed test at a = .01? (Round your answer to 3 decimal places.) t-value =

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter3: Straight Lines And Linear Functions

Section3.4: Linear Regression

Problem 12SBE: Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4

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Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
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The superintendent of a school district wanted to predict the percentage of students passing a sixth-grade proficiency test. She obtained the data on percentage of students passing the proficiency test (% Passing), mean teacher salary in thousands of dollars (Salaries), and instructional spending per pupil in thousands of dollars (Spending) of 47 schools in the state. Following is the multiple regression output with Y = % Passing as the dependent variable, X, = Salaries and X, = Spending. Click the icon to view the results. Determine whether the following statement is true or false: You can conclude definitively that mean teacher salary individually has no impact on the mean percentage of students passing the proficiency test, taking into account the effect of instructional spending per pupil, at a 1% level of significance based solely on but not actually computing the 99% confidence interval estimate for B, - X Regression Statistics O False Regression Statistics Multiple R 0.4276 True…
A real estate company wants to study the relationship between house sales prices and some important predictors of sales prices. Based on data from recently sold homes in the space, the following variables are used in a multiple regression model. y sales price (in thousands of dollars) x₁ = total floor area (in square feet) X₂= number of bedrooms x3² distance to nearest high school (in miles) The estimated model is as follows. y=121 +0.083x₁ +23x₂ - 4x3 Answer the questions below for the interpretation of the coefficient of x₁ in this model. (a) Holding the other variables fixed, what is the average change in sales price for each 100-square-foot increase in floor area? dollars (b) Is this change an increase or a decrease? increase decrease X Ś
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The superintendent of a school district wanted to predict the percentage of students passing a sixth-grade proficiency test. She obtained the data on percentage of students passing the proficiency test (% Passing), mean teacher salary in thousands of dollars (Salaries), and instructional spending per pupil in thousands of dollars (Spending) of 47 schools in the state. Following is the multiple regression output with Y= % Passing as the dependent variable, X, = Salaries and X, = Spending. E Click the icon to view the multiple regression output. Determine whether the following statement is true or false: The null hypothesis Hn: B, = B, = 0 implies that percentage of students passing the proficiency test is not related to one of the explanatory variables. Multiple Regression Output True False Regression Statistics Multiple R 0.4276 R Square 0.1828 Adjusted R Square 0.1457 Standard Error 5.7351 Observations 47 ANOVA df SS MS F Significance F Regression 323.8284 161.9142 4.9227 0.0118…
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The superintendent of a school district wanted to predict the percentage of students passing a sixth-grade proficiency test. She obtained the data on percentage of students passing the proficiency test (% Passing), mean teacher salary in thousands of dollars (Salaries), and instructional spending per pupil in thousands of dollars (Spending) of 47 schools in the state. Following is the multiple regression output with Y = % Passing as the dependent variable, X, = Salaries and X, = Spending. E Click the icon to view the results. Determine whether the following statement is true or false: You can conclude definitively that mean teacher salary individually has no impact on the mean percentage of students passing the proficiency test, taking into account the effect of instructional spending per pupil, at a 1% level of significance based solely on but not actually computing the 99% confidence interval estimate for B1. Regression Statistics O False Regression Statistics Multiple R 0.4276 O…