The output of a another regression analysis on the effect of radio advertising spending, television advertising spending and online advertising spending onsales is given below. For this study they explored 3 different types of advertising spending (radio, television and online). They modelled it asy = ao + a1¤1+a2x2 + a3X3. The table below gives the summary output of this regression analysis.Regression Analysis: Sales versus SpendAnalysis of VarianceSourceDFsMSF-ValueP-ValueRegressiond freg23.897.37MSRF-valp-valErrordferr552.44MSETotal36Find the F-value in the above table. Give your answer to 3 decimal places.

There are three different types of advertising spending. That is, p=3. The regression degrees of…

Answered: The output of a another regression…

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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2. Following data is amount of Assessed Value for an office building for a given floor area, number of office space, number of entrances, and the age of the offic building. Use excel to …. Obtain a Scatter plot of Floor Area as the independent and Assessed value as the dependent variable. Note the linear regression Model Predict the assessed value for 6000 sq ft. FloorArea (Sq.Ft.) Offices Entrances Age AssessedValue ($'000) 4790 4 2 8 1796 4720 3 2 12 1544 5940 4 2 2 2094 5720 4 2 34 1968 3660 3 2 38 1567 5000 4 2 31 1878 2990 2 1 19 949 2610 2 1 48 910 5650 4 2 42 1774 3570 2 1 4 1187 2930 3 2 15 1113 1280 2 1 31 671 4880 3 2 42 1678 1620 1 2 35 710 1820 2 1 17 678 4530 2 2 5 1585 2570 2 1 13 842 4690 2 2 45 1539 1280 1 1 45 433…
Home Sale Prices. Regarding the relationship between the sale price of a home and the predictor variables size in square feet and type of roof (tile or non-tile). In that exercise, we considered the regression of price on size and roof, the indicator variable for type of roof. a. Obtain a plot of price versus size with different plot symbols for homes having a tile roof and for homes having a non-tile roof. Based on this plot, does it appear that roof is a useful predictor variable? Explain your answer. b. Obtain the regression analysis of price on size and roof. Conduct the t-tests for the individual utility of the two predictor variables at the 5% level of significance. Interpret your results. c. Based on the output in part (b), obtain the individual regression equations relating price to size for homes having tile roofs and for homes having non-tile roofs. d. Obtain plots of residuals versus fitted values, residuals versus size, residuals versus roof, and a normal probability plot…
Are the years of education of a child dependent on the years of education of their parent? The table shows the number of years of education of parent and the number of years of education of their child. Years of Education of Parent 13 9 7 12 12 10 11 Years of Education of their Child 13 11 7 16 17 9 17 If there is a significant linear correlation between the variables, determine the regression equation. Are the years of education of a child dependent on the years of education of their parent? The table shows the number of years of education of parent and the number of years of education of their child. Years of Education of Parent 13 9 7 12 12 10 11 Years of Education of their Child 13 11 7 16 17 9 17 If there is a significant linear correlation between the variables, determine the regression equation. y’ = 1.5x - 3 There is no significant correlation between the variables,…
Is there a relationship between the weight and price of a mountain bike? The following data set gives the weights and prices for ten mountain bikes. Let the expanatory variable x be the weight in pounds and the response variable y be the bike's price. Weight (LB) 32 33 29 29 34 37 28 30 34 30 Price ($) 980 350 430 710 930 160 590 530 180 1090 a. Construct a scatterplot. Interpret. b. Find the regression equation. Interpret the slope in context. Does the y-intercept have contextual meaning? c. You decide to purchase a mountain bike that weighs 33 pounds. What is the predicted price for the bike? a. Which scatterplot below correctly shows the data? A. 254001200xy A coordinate system has a horizontal x-axis labeled from 25 to 40 in increments of 1 and a vertical y-axis labeled from 0 to 1200 in increments of 50. A cluster of plotted points that form a line that falls from left to…
The accompanying table shows a portion of data that refers to the property taxes owed by a homeowner (in $) and the size of the home (in square feet) in an affluent suburb 30 miles outside New York City. Click here for the Excel Data File Taxes Size 21,987 2,403 17,353 2,451 29,238 2,866 a. Estimate the sample regression equation that enables us to predict property Taxes on the basis of the size of the home. (Round your answers to 2 decimal places.) Taxes = + Size. b. Interpret the slope coefficient. O As Property Taxes increase by 1 dollar, the size of the house increases by 6.71 ft. O As Size increases by 1 square foot, the property taxes are predicted to increase by $6.71. c. Predict the property Taxes for a 1,400-square-foot home. (Round coefficient estimates to at least 4 decimal places and final answer to 2 decimal places.) Taxes
Listed below are paired data consisting of movie budget amounts and the amounts that the movies grossed. Find the regression equation, letting the budget be the predictor (x) variable. Find the best predicted amount that a movie will gross if its budget is $105 million. Use a significance level of a = 0.05. Budget ($)in Millions Gross ($) in Millions 41 23 114 75 78 47 120 64 10 59 127 22 12 150 2 0 127 18 111 65 113 112 102 94 64 98 211 41 22 288 57 Click the icon to view the critical values of the Pearson correlation coefficient r. ..... x. (Round to one decimal place as needed.) The regression equation is = + The best predicted gross for a movie with a $105 million budget is $ million. (Round to one decimal place as needed.)
PVan

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