Consider the following summary output, which was generated from a sample of 8 employees relating age to annual salary.SUMMARY OUTPUTRegression StatisticsMultiple R0.138089232R Square0.019068636Adjusted R Square-0.144419925Standard Error1.46902996Observations8.ANOVAdfSSMSFRegression0.2517060.2520.116775Residual6.12.9482942.158Total13.2wkes Learning ANOVAdfSSMSFRegression10.2517060.2520.116775Residual6.12.9482942.158Total13.2CoefficientsStandard Errort StatP-valueIntercept3.1599591422.657367821.1891310.27931Age0.02267620.0663978940.341520.744355Step 2 of 2: What percentage of the variation in annual salary is explained by the model? Round your answer to two decimal places.

From the given data R^2 = ? R^2 = 0.019068636

Answered: Consider the following summary output,…

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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A statistical program is recommended. Jensen Tire & Auto is in the process of deciding whether to purchase a maintenance contract for its new computer wheel alignment and balancing machine. Managers feel that maintenance expense should be related to usage, and they collected the following information on weekly usage (hours) and annual maintenance expense (in hundreds of dollars). Weekly Usage(hours) AnnualMaintenanceExpense 13 17.0 10 22.0 20 30.0 28 37.0 32 47.0 17 30.5 24 32.5 31 39.0 40 51.5 38 40.0 #1) Develop the estimated regression equation that could be used to predict the annual maintenance expense (in hundreds of dollars) given the weekly usage (in hours). (Round your numerical values to two decimal places.) #2) The expected expense of a machine being used 34 hours per week is $ hundred.
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. A professor at the University of Iowa was interested in evaluating whether domestic dispute calls were more dangerous to officers than other types of calls. Collecting information on call for service and whether the call resulted in officer injury. The data is displayed in the contingency table below. Type of Call Domestic Dispute Not a Domestic Dispute Officer Injury No 128 675 Yes 245 786 Using the information to complete Table 1 and answer the questions below. Table 1. Chi-square Category Observed Expected O – E (O – E)2 (O – E)2/E No, Domestic 128 163.31 -35.31 1246..796 7.64 No, Not Domestic 675 639.69 35.31 1246.796 1.95 Yes, Domestic 245 209.69 35.31 11506.85 5.951.52 Yes, Not Domestic 786 821.31 -35.31 1246.796 Using an alpha level of 0.05, are domestic calls more dangerous for officers than other types of calls? Compute…
Suppose the following table was generated from the sample data of 20 teachers relating annual salary to months of teaching experience and gender. Coefficients Standard Error t Stat P-Value Intercept 39356.558109 323.427410 121.685908 0.000000 Months of Experience 58.906471 7.654770 7.695394 0.000001 Male (1 if male, 0 if female) 759.880847 241.719905 3.143642 0.005923 Step 1 of 2: In this regression equation, what is the intercept value for women? Enter your answer in the space provided. Do not round your answer. Step 2 of 2: In this regression equation, what is the intercept value for men? Enter your answer in the space provided. Do not round your answer.
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An agent for a residential real estate company in a large city has the business objective of developing more accurate estimates of the monthly rental cost for apartments. Toward that goal, the agent would like to use the size of an apartment, as defined by square footage to predict the monthly rental cost. The agent selects a sample of 25 apartments in a particular residential neighborhood and collects the following data: Size (square feet) Rent ($) 850 1950 1450 2600 1085 2200 1232 2500 718 1950 1485 2700 1136 2650 726 1935 700 1875 956 2150 1100 2400 1285 2650 1985 3300 1369 2800 1175 2400 1225 2450 1245 2100 1259 2700 1150 2200 896 2150 1361 2600 1040 2650 755 2200 1000 1800 1200 2750 Make a Normal Probability Plot and a Residual plot of the Residuals (Y axis) vs. Apartment Size (X axis). Based on these results,…
An agent for a residential real estate company in a large city has the business objective of developing more accurate estimates of the monthly rental cost for apartments. Toward that goal, the agent would like to use the size of an apartment, as defined by square footage to predict the monthly rental cost. The agent selects a sample of 25 apartments in a particular residential neighborhood and collects the following data: Size (square feet) Rent ($) 850 1950 1450 2600 1085 2200 1232 2500 718 1950 1485 2700 1136 2650 726 1935 700 1875 956 2150 1100 2400 1285 2650 1985 3300 1369 2800 1175 2400 1225 2450 1245 2100 1259 2700 1150 2200 896 2150 1361 2600 1040 2650 755 2200 1000 1800 1200 2750 (a) Construct a scatter plot. (b) Use the least-squares method to determine the regression coefficients (intercept and slope). (c)…

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