A life insurance company wishes to examine the relationship between the amount of life insurance held by a familyand family income. From a random sample of households, the company collected the accompanying data. The dataare in units of thousands of dollars. (See worksheet INSUR)Let12345678abсd3bсdabсdabсdbсdbсdabссdbсdсd10abсd11bсd12abCdThe numerator of the slope coefficient formula for the estimated regression equation is:265.202.84270.615.14276,137.90281,773.37The denominator of the slope coefficient formula for the estimated regression equation is:66,646.9868,007.1269,395.0270,811.259 The sum of squared explained deviations (SSR) is,a1,098,812.8b 1,121,237.61,144,120.01,167,469,4The vertical intercept of the estimated regression equation is-8.8241-7.6731-6.6723-5.80203.4514.0604.7775.620The estimated regression equation predicts that for each additional $1,000 income life insurance policy will riseby($1,000)239.274249.243259.629The income of one policy holder is 58 ($1000). The predicted life insurance policy is229.703y=x=7.5078.3419.26810.297The observed policy amount for the policy holder in previous question is 240 ($1,000).The prediction error isThe sum of squared errors (SSE) is,28,567.029,757.330,997.232,288.7INSURINCOMEThe sum of squared total (SST) is,1,150,994.91,174,484.61,198,453.61,222,911.9The sample data provides that0.97410.93670.90070.8660The observed insurance policy deviates from the predicted policy, on average, by25.99026.79427.62328.4770.07720.08580.09530.1059($1,000)($1,000)fraction variations in the life insurance policy is explained by income.For the purpose of statistical inference for the slope parameter, the standard error of the slope coefficient, se(b,),is INSUR INCOME911182532474012911692067091382464434391913876361751401452404124352577354224602003916891092522353862931951791451462354354472929636811668354016440571071015197169464239581111065817111210554110170286462109694546414059105108

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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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Bluereef real estate agent wants to form a relationship between the prices of houses, how many bedrooms, House size in sq ft and Lot Size in sq ft. The data pertaining to 100 houses were processed using MINITAB and the following is an extract of the output obtained: The regression equation is Price = B + Bedroom + yHouse Size + ALot Size Predictor Coef SE Coef T P Constant 37718 2.66 ** Bedrooms 2306 0.33 74.3 -4.36 House Size Lot Size S-25023 Error Total R-Sq-56.0 % 96 99 14177 6994 52.98 17.02 0.742 0.164 -0.26 0.798 Source DE SS MS F Regression 3 76501718347 25500572782 *** Residual 60109046053 626135896 R-Sq (adj) -54.6% P d) Is y significantly different from -0.5? e) Perform the F test at the 1% level, making sure to state the null and alternative hypoteses. f) Give an interpretation to the term “R-sq” and comment on its value.
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How can the coefficient of determination be interpreted?
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 R? = 0.9695 250 200 150 100 50 1920 -50 1940 1960 1980 2000 2020 Year Write a sentence explaining the value of the slope for this regression line. For every increase in year, the number of vehicle registrations in the US increases by 3.0161 million. For every increase in year, the number of vehicle registrations in the US increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 5819.5. For every increase in vehicle registrations in the US, the number of years increases by 3.0161 million. Registrations (in millions)
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A marketing analyst wants to examine the relationship between sales (in $1,000s) and advertising (in $100s) for firms in the food and beverage industry and so collects monthly data for 25 firms. He estimates the model: Sales = Bo + B1 Advertising + ɛ. The following table shows a portion of the regression results. Coefficients Standard Error t-stat p-value Intercept 41.1 13.88 2.961 0.0046 Advertising 2.72 1.7 -1.6 0.0586 When testing whether the slope coefficient differs from 3, the value of the test statistic is Multiple Choice t23 = 1.809 t23 = 0.165 t23 = -0.165 t23 =-1.809
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