The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue () as a function of television advertising (31) and newspaper advertising Weekly Gross Television Newspaper Revenue Advertising Advertising ($10005) ($1000s) ($1000s) 97 6.0 1.5 90 2.0 3.0 96 5.0 1.5 92 2.5 2.5 95 4.0 4.3
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- Use the scatterplot of Vehicle Registrations below to answer the questions Vehicle Registrations in the United States, 1925- 2011 Vehicles millions 300 y = 3.0161x - 5819.5 R² = 0.9695 250 200 150 100 50 1920 -50 1940 1960 1980 2000 2020 Year State the trend line (regression line). y= 3.0161 x -5819.5 year number of vehicle registrations R^2 = 0.9695 not enough information to determine Registrations (in millions)What does it mean for a regression line to be the "best-fit" line.A microcomputer manufacturer has developed a regression model relating his sales (y=$10,000s) with three independent variables. The three independent variables are price per unit(Price in $100s), advertising( ADV in $1000s) and the number of product lines (Lines). Part of the regression results is shown below. Coefficient Standard Error Intercept 1.0211 22.8752 Price(X1) -0.1524 0.1411 ADV (X2) 0.8849 0.2886 Lines(X3) -0.1463 1.5340 Source d.f. S.S. Regression 3 2708.61 Error 14 2840.51 Total 17 5549.12 What has been the sample size (n) for this analysis? Use the above results to find the estimated multiple…
- A researcher uses a regression equation to predict home heating bills (dollar cost), based on home size (square feet). The correlation between predicted bills and home size is 0.70. What is the correct interpretation of this finding? (A) 70% of the variability in home heating bills can be explained by home size. (B) 49% of the variability in home heating bills can be explained by home size. (C) For each added square foot of home size, heating bills increased by 70 cents. (D) For each added square foot of home size, heating bills increased by 49 cents. (E) None of the above.The owner of Showtime Movie Theaters, Inc., used multiple regression analysis to predict gross revenue (y) as a function of television advertising (x1) and newspaper advertising (*2). Weekly Gross Television Newspaper Revenue Advertising Advertising ($1000s) ($1000s) ($1000s) 96 6.0 2.5 90 2.0 3.0 96 5.0 2.5 92 3.5 2.5 96 4.0 3.3 95 3.5 3.3 94 2.5 4.2 95 4.0 3.5 The estimated regression equation was ŷ = 79.4 + 1.94x1 + 2.40x2. The computer solution provided SST = 33.5 and SSR = 29.283. a. Compute and interpret R2 and R. (to 3 decimals). R2 = R = b. When television advertising was the only independent variable, R = 0.653 and R = 0.595. Do you prefer the multiple regression results? Explain. No, because less variability is explained when both independent variables are usedThe consumption function captures one of the key relationships in economics. It expresses consumption as a function of disposal income, where disposable income is income after taxes. The attached file "Regression-Dataset1" shows data of average US annual consumption (in $) and disposable income (in $) for the years 2000 to 2016. a)what is the Pearson correlation value between income and consumption? Select one: Ⓒa. 0.978 b. 0.109 c. None of the above d. 0.791
- Describe about how to place a regression line?The following data table shows the historical data for the first semester 2020, of the amount of sales of the company "IRC", which sells sneakers. Utilizing multiple lineal regression (as shown on the image), find an equation that estimates the number of sneakers sold by the company, based on advertising and revenue. Also, determine the standard error of estimation, the coefficient of determination, and the correlation coefficient. Write down what was the quantity in thousands sold in July if the amount of ads was 8 and the income for each unit was $135To determine if the listing price of a house influences the selling price; a financial analyst sampled fifty houses and collected data on sale price,Y,(in $’000) and listed price,X,(in$’000) and fitted a regression model to the data
- Suppose that for a typical FedEx package delivery, the cost of the shipment is a function of the weight of the package measured in ounces. You want to try to predict the cost of a typical shipment given package dimensions. If 10 packages in a city are sampled and the regression output is given below, report the regression equation. 1) (cost of delivery) = 1.468*(weight) - 23.015 2) (weight) = -23.015*(cost of delivery) + 1.468 3) (cost of delivery) = -23.015*(weight) + 1.468 4) (cost of delivery) = 1.468*(weight) 5) (weight) = 1.468*(cost of delivery) - 23.015Suppose you are estimating a wage regression, where salary is the dependent variable and age, years of education and a dummy variable for male are your independent variables. You are interested in measuring how salary differs between those who have at least a college education with those who have less than a college education. If a person is considered as having a college education when she has more than 12 years of education, how can you measure the difference in salary between college and non-college educated individuals? Select one: a. Multiply coefficient for years of education in original regression by 12 O b. Re-estimate model replacing years of education with a dummy variable for college c. Re-estimate model replacing years of education with a dummy variable for college and one for no college O d. Re-estimate model interacting years of education with a dummy variable for college e. Calculate the difference in predicted salary between an individual with 14 years of education and…The consumption function captures one of the key relationships in economics. It expresses consumption as a function of disposal income, where disposable income is income after taxes. The attached file “Regression–Dataset1” shows data of average US annual consumption (in $) and disposable income (in $) for the years 2000 to 2016. a)what is the Pearson correlation value between income and consumption? Select one: a. 0.791 b. 0.109 c. None of the above d. 0.978