A sales manager for an advertising agency believes there is a relationship between the number of contacts that a salespersonmakes and the amount of sales dollars earned. A regression analysis shows the following results:Coefficients Standard Errort-Statp-valueIntercept-12.2016.560-1.8600.100Number of contacts2.1950.17612.5050.000What is the slope of the linear equation?Multiple Choice-12.201-1.86012.505

The regression line equation is given by = a + bx

Answered: A sales manager for an advertising…

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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please assist, the question states to "click on the datafile logo to reference the data" but the data is listed already in the question. when clicking that link, it opens up the same information in excel so please do not reject because the data is there already.
A sales manager for an advertising agency believes that there is a relationship between the number of contacts that a salesperson makes and the amount of sales dollars earned. A regression analysis shows the following results. Coefficients Standard Error t-Stat p-value Intercept −12.201 6.560 −1.860 0.100 Number of contacts 2.195 0.176 12.505 0.000 What is the Y-intercept of the linear equation? Multiple Choice −12.201 2.195 −1.860 12.505
You run a regression of Iowa crop yield per acre on average growing season temperature, average growing season rainfall, and average growing season total precipitation. You get the following results: Data Table Variable Coefficient Std. Error t value p-value (Intercept) 103.4183 42.891 2.411 0.0161 Temp 1.9446 0.0636 30.577 0.000001 Rain 43.988 21.1693 2.078 0.038 Precipitation −46.5995 21.1768 −2.2 0.028 What problem(s) do you think this regression has? Group of answer choices a) Omitted variable of how much fertilizer was used. This will impact the Rain coefficient. b) Multi-collinearity. Rain and precipitation are very highly correlated, their estimates are unreliable. c) Huge outliers are driving the result from years in drought. d) No issues, regression is probably fine.
Write your complete solutions and box your answers. Regression methods were used to analyze the data from a study investigating the relationship between roadway surface temperature (x) and pavement deflection (y). Summary quantities were n = 20, Σy = 12.75, Σy =8.86, Σ.x; = 1478, Σx = 143,215.8, and Σ.xy = 1083.67. (a) What change in mean pavement deflection would be expected for a 1°F change in surface temperature? (b) Test for significance of regression using a = 0.05. Find the (c) P-value for this test. What conclusions can you draw? Estimate the standard errors of the slope and intercept.
The computer output (below) shows a relationship where Y = Sale price for a home, X1 = living area, and X2 = # of bedrooms, X3 = # of bathrooms. We would like to predict Price (Y). There are three 2-variable regression relationships shown and one 4-variable multiple regression relationship shown. Regression Equation Price = 171032 + 120420 Bathrooms Model Summary S R-sq R-sq(adj) R-sq(pred) 267458 14.27% 14.17% 13.82% Regression Equation Price = 200274 + 113.68 Living Area Model Summary S R-sq R-sq(adj) R-sq(pred) 268449 13.54% 13.44% 13.10% Regression Equation Price = 338975 + 40234 Bedrooms Model Summary S R-sq R-sq(adj) R-sq(pred) 286741 1.35% 1.24% 0.92% **Multiple regression output is below: Regression Equation Price = 275641 + 84.7 Living Area - 66797 Bedrooms + 93925 Bathrooms Model Summary S R-sq R-sq(adj) R-sq(pred) 260320 18.97%…
The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x 1) and newspaper advertising (x 2). The estimated regression equation was Weekly Gross Revenue ($1000s) Televison Advertising ($1000s) Newspaper Advertising ($1000s) 97 6 1.5 91 3 2 95 5 2.5 93 3.5 2.5 96 4 4.3 94 4.5 2.3 95 3.5 4.2 95 4 3.5 ŷ = 82.5 + 2.01 x 1 + 1.26 x 2The computer solution provided SST = 24 and SSR = 22.876. Compute R 2 and R a 2 (to 3 decimals). R 2 R a 2 When television advertising was the only independent variable, R 2 = 0.551 and R a 2 = 0.476. Are the multiple regression analysis results preferable?
-by-Side We expect a car's highway gas milcage to be related to its city gas mileage (in miles per gallon, mpg). Data for all 1259 vehicles in the government's 2019 Fuel Ecomomy Guide give the regression line (b) What is the intercept? Give your answer to three decimal places. highway mpg - 8.720 + (0.914 x city mpg) intercept: mpg for predicting highway milcage from city mileage. Why is the value of the intercept not statistically meaningful? O The value of the intercept represents the predicted highway milcage for city gas mileage of 0 mpg. and such a prodiction would be invalid since O is outside the range of the data. O The value of the intercept represents the predicted city mileage for highway gas mileage of 0 mpg. and such a car does not exist. The value of the intercept is an average value calculated from a sample. The value of the intercept represents the predicted highway milcage for slope 0.
You are conducting a multiple regression analysis to determine if there is a linear relationship between y, the number of applications to in-state universities and two factors: ×1, the state's unemployment rate and ×2, the average grant provided to in-state students. Ten observations are available. The analysis produced the estimated regression equation below. y = 6.5 + 2.2×1 + 4.6×2 The standard error for the intercept, unemployment rate are 9.34, and 1.23, respectively. Is the coefficient for the unemployment rate variable statistically significant at the 5% significance level? Explain. A) No, since stat = 1.39 for this coefficient, which is less than 2.365. B) No, since the p-value for this coefficient is .072, which is greater than 05 C) None of these D) No, since the p-value for this coefficient is .072, which is greater than .05
A sales manager for an advertising agency believes there is a relationship between the number of contacts that a salesperson makes and the amount of sales dollars earned. A regression analysis shows the following results. Coefficients Standard Error t-Stat p-value Intercept −12.201 6.560 −1.860 0.100 Number of contacts 2.195 0.176 12.505 0.000 What is the decision regarding the hypothesis that the slope is different from zero? Assume the level of significance is 0.05. Multiple Choice Fail to reject the null hypothesis. We conclude the slope is equal to zero. Fail to reject the alternative hypothesis. We conclude the slope is not equal to zero. Reject the null hypothesis. We conclude that the slope is not equal to zero. Reject the alternative hypothesis. We conclude that the slope is equal to zero.
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…
Data was collected for a regression analysis where sleep quality (as a percentage) depends on the amount of caffeine consumed in a day (measured in mg). bo was found to be 92.7, b₁ was found to be -0.76, and R² was found to be 0.86. Interpret the slope of the line. O On average, each one mg increase in caffeine consumed increases a person's sleep quality by 92.7%. O On average, when x = = 0, a person has a sleep quality of -0.76%. O On average, each one mg increase in caffeine consumed decreases a person's sleep quality by 0.76%. On average, when x = 0, a person has a sleep quality of 92.7%. O We should not interpret the slope in this problem. O We should interpret the slope in this problem, but none of the above are correct.
answer both please and explain well. Anna company sells coffee products to various customers. In recent years, profits have been declining. The CFO of the company investigated the reasons for the profit decline and performed regression analysis for sales and costs. The CFO determined that sales depend on product price, delivery speed, customer services, and marketing expenses. She also determined that total costs consist of variable costs of $25 per unit and fixed costs of $56,000. Marketing expenses have a coefficient of determination of 75% related sales. Questions 1. Define the coefficient of determination and explain what it means in this scenario. 2. Express the relationship between total costs and variable costs for Anna Company using a regression equation. Explain each element of the equation.

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