The results shown to the right provide the X-values, residuals, and a residual plot from a regression analysis. Is there any evidence of a pattern inKthe residuais? ExplainChoose the correct answer belowOA You Befeudus show decreasing variationOB. Yes, the residuals show a distinct cyclical pattomOC No, the residuals appear to be randomly spreadOD Yes, the residuais show a disdect curved pattern234X15671910Residuals0.69-0.88116-0.66242-0.790.20163-111178WAPDAMy214offO(25

The values corresponding to the X-variable, residuals are provided…

Answered: he results shown to the right provide…

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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Waterbury Insurance Company wants to study the relationship between the amount of fire damage and the distance between the burning house and the neorest fire station. This information will be used in setting rates for insurance coverage. For o somple of 30 claims for the last year, the director of the actuarial department determined the distance from the fire station (x) and the amount of fire domage, in thousands of dollars (y). ANOVA table Source Regression Residual SS df MS F 1,870.5782 1,870.5782 41.39 1,265.4934 3,136.0716 28 45.1962 Total 29 Regression output Standard Variables Coefficients Error t(df-28) Intercept Distance-X 13.76815 3.106 2.914 3.77es e. 5861 6.43 Click here for the Excel Data File a-1. Determine the regression equation. (Round your answers to 3 decimal places.) y3D X. a-2 Is there a direct or indirect relotionship between the distance from the fire station and the amount of fire damage? The relationship between distance and damage is b. How much domage would…
A researcher's results are shown below using Femlab(labor force participation rate among females) to try to predict Cancer (death rate per 100,000 population due to cancer) in the 50 US states. What is the R2 for this regression? Source of variation df ss ms f Regression 1 5377.836 5377.836 5.228879 residual 48 49367.389 1028.487 total 49 54745.225
R2
The commercial division of a real estate firm is conducting a regression analysis of the relationship between x, annual gross rents (in thousands of dollars), and y, selling price (in thousands of dollars) for apartment buildings. Data were collected on several properties recently sold and the following computer output was obtained. Analysis of Variance SOURCE DF Adj SS Regression 1 41587.3 Error 7 Total 8 51984.1 Predictor Coef SE Coef T-Value Constant 20.000 3.2213 6.21 X 7.210 1.3626 5.29 Regression Equation Y = 20.0 + 7.21 X (a) How many apartment buildings were in the sample? (b) Write the estimated regression equation. ŷ = (c) What is the value of sb1? Find the value of the test statistic. (Round your answer to two decimal places.) Find the p-value. (Round your answer to three decimal places.) p-value =
Using the regression model from the previous problem, what is the interpretation of the slope coefficient associated with Age? Assume Salary is measured in $1,000's.
What is the least-squares regression line with the point (9,13) included in the data set? Data Set x y 3 6 4 5 5 7 7 6 8 9 8 8 10 8 11 9 11 7 12 10 13 12 13 10 14 11 This is a reading assessment question. ..... y hat = ______x + ______ Type integers or decimals rounded to 4 decimal places as needed
In the below residual plot, which assumption(s) of regression is/are violated? -4 Residuals -2 0 2 Residuals vs Fitted 00 8080 00 08 810 300 049 -8 -6 -4 -2 -2 0 2 4 6 Fitted values Equal variance across levels of X Normality Residuals are independent Linear relationship between X and Y
Gerardo is investigating how long his phone's battery lasts (in hours) for various brightness levels (on a scale of 0-100). His data is displayed in the table and graph below. Hours 10+ 9 8 7 6 3 2 1 Brightness Level (x) 16 Hours (y) 10 20 30 37 31 6.7 5.8 5.2 Submit Question -1 What is the residual for the point (58,7.1)? hours Rejected Questions 40 50 Brightness Level 37 4 60 70 44 5.9 80 58 7.1 77 5.1 99 4.2 90 100 110 Math Statistics
An automobile rental company wants to predict the yearly maintenance expense (Y) for an automobile using the number of miles driven during the year () and the age of the car (, in years) at the beginning of the year. The company has gathered the data on 10 automobiles and run a regression analysis with the results shown below:. Summary measures Multiple R 0.9689 R-Square 0.9387 Adj R-Square 0.9212 StErr of Estimate 72.218 Regression coefficients Coefficient Std Err t-value p-value Constant 33.796 48.181 0.7014 0.5057 Miles Driven 0.0549 0.0191 2.8666 0.0241 Age of car 21.467 20.573 1.0434 0.3314 Use the information above to estimate the annual maintenance expense for a 10 years old car with 60,000 miles.
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Thirty-four automobiles were tested for fuel efficiency (in miles per gallon). The following frequency distribution was obtained. Find the variance and standard deviation. Round your answers to at least one decimal place. Class boundaries Frequency 7.5 – 12.5 3 12.5 – 17.5 9 17.5 – 22.5 14 22.5 – 27.5 7 27.5 – 32.5 1 Variance = Standard deviation =

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