What is the value of residual sum of squares A 117599 B 101305 C 109452 D

What is the value of residual sum of squares a 117599

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16) What is the value of residual sum of squares?A) 11,759.9B) 10,130.5C) 10,945.2D) 36,935.817) What is the value of total sum of squares?18) What is the value of significanceF?19) What is the regression coefficient ofy-intercept?20) What is the standard error of estimate?A) 0.66B) 0.76C) 0.61D) 0.8521) The residual is defined as the difference between the:ESSAY. Write your answer in the space provided or on a separate sheet of paper.The results of a regression analysis are listed below but, unfortunately, some values as identified by asterisks aremissing.SUMMARY OUTPUTRegression StatisticsMultiple R0.187R Square*Adjusted R SquareStandard Error*Observations115.000ANOVAdfSSMSFSignificance FRegression1.000*130433116.219*0.046Residual113.000 3609911959.868*Total114.0003740345076.087CoefficientsStandard Errort StatP-valueIntercept10725.8021535.2156.9870.000Age*34.6252.021*22) Calculate the coefficient of determination23) Determine the mean square error4
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24) Determine the standard error of estimate25) Calculate the regression sum of squares26) What is the value of the test statisticF?27) Calculate the slope coefficient.28) What is thep-value associated with the independent variable age?29) For a random sample of 263 professionals, the correlation between their age and their income was found tobe 0.17. Use 0.05 level of significance to test the null hypothesis hat there is no linear relationship betweenthese two variables against the alternative that there is a positive relationship.MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.A real estate appraiser is interested in determining the factors that determine the price of a house. She wants to run thefollowing regression:Y=Ά0+Ά1X1+Ά2X2+Ά3X3whereY=price of the house in $1,000s,X1=number of bedrooms,X2=square footage ofliving space, andX3=number of miles from the beach. Taking a sample of 30 houses, the appraiser runs a multipleregression and get the following results:Y^=123.2+4.59X1+0.125X2-6.04X3,Sb0=103.2,Sb1=2.13,Sb2=0.062,Sb3=4.17,R2=0.47, andR2=0.45 (adjusted).30) What should the null and alternative hypotheses be forΆ1?
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