Consider the following regression estimates (FN8)SourcedfMSNunber of obs500%3DF(2, 497)100.85Model71007499.52 35503749.8Prob > F0.0000Residual174967111497 352046.502Total245974611499 492935.092incomeCoef.Std. Err.tP>|t|(95% Conf. Interval]female-37.571953.55403-0.700.483-142.792167.6483hours18.793741.34566913.970.00016.1498421.43765„cons302.97547.652956.360.000209.349396.6011What is the R-squared of the regression above?Please stote the onswer as a value between O and 1.

The formula for coefficient of determination or R-squared is, R2 = SSModel/SSTotal.

Answered: Consider the following 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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Hi Just question 10 and 11 Thank you.
The following is a partial computer output of a multiple regression analysis of a data set containing 20 sets of observations on the dependent variableThe regression equation isSALEPRIC = 1470 + 0.814 LANDVAL + 0.820 IMPROVAL + 13.5 AREA Predictor Coef SE Coef T P Constant 1470 5746 0.26 0.801 LANDVAL 0.8145 0.5122 1.59 0.131 IMPROVAL 0.8204 0.2112 3.88 0.0001 AREA 13.529 6.586 2.05 0.057 S = 79190.48 R-Sq = 89.7% R-Sq(adj) = 87.8% Analysis of Variance Source DF SS MS Regression 3 8779676741 2926558914 Residual Error 16 1003491259 62718204 Total 19 9783168000 For the problem above, we want to carry out the significance test about the coefficient of LANDVAL, what is the t-value for this test, and is it significant? 46.66, significant 2.05, significant 1.59, not significant 0.26, not significant
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…
If a regression model of the form y= B,+B,x,+... + B,x, is fit to 132 observations on each variable and yields an R´value of 0.87, fill in the blanks in the following ANOVA table. Do all calculations to at least three decimal places. Source of Degrees of freedom Sums of Mean F statistic variation squares squares Regression 69 Error Total
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
The following output comes from regression using the actual HW9 scores and the Final test scores from intro stats one semester. Sample size: 50R (correlation coefficient) = 0.3658R-sq = 0.1338Estimate of error standard deviation: 10.36256Parameter estimates: Parameter Estimate Std. Err. DF T-Stat P-Value Intercept 43.558118 11.1716 48 3.899 0.0003 Slope 0.360048 0.132225 48 2.723 0.009 Assume no assumptions are violated. Form a 87% Confidence interval for how much your final is supposed to increase for each problem done on homework 9.Use 5 decimal places
Using the regression model from the previous problem, what is the interpretation of the slope coefficient associated with Age? Assume Salary is measured in $1,000's.
Consider the following regression estimates (FN4) Linear regression 29,471 318.65 = 0.0000 = 0.0108 = 801.34 Robust income Coef. Std. Err. t P>|t| [95% Conf. Interval] female -167.6086 9.389494 -186.0124 -149.2047 -17.85 0.000 60.38 0.000 _cons 946.3256 15.67369 915.6045 977.0468 where income is weekly income in NZ$, female is equal to 1 if the person if female and 0 if the person is male. What is the average income of all males in this regression? Please only state the number. Do not use the $ sign in your answer. Number of obs F(1, 29469) Prob > F R-squared Root MSE
What is the residual for this (size = 240) observation? Round to 2 decimals
Consider the following regression estimates (FN6) Source SS df MS 526 64.11 Model 1927.87673 3 642.625576 0.0000 Residual 5232.53756 522 10.0240183 0.2692 0.2650 Total 7160.41429 525 13.6388844 3.1661 wage Coef. Std. Err. t P>|t| [95% Conf. Interval] educ .5953429 .0530251 11.23 0.000 .4911741 .6995118 exper .268287 .0368969 0.000 .1958023 .3407717 7.27 -5.61 0.000 exper2 -.0046123 .000822 -.006227 -.0029975 _cons -3.96489 .7521526 -5.27 0.000 -5.442508 -2.487272 where wage is hourly wage in US$, educ is years of education, exper is years of work experience and exper2 is experience squared (exper * exper). At how many years is the marginal effect of increasing experience on predicted wage equal to zero? Only state the number in your answer (e.g. don't write US$ or $ or years). Number of obs = F(3, 522) = Prob > F R-squared Adj R-squared = Root MSE 11

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