1The K3 Estate Ltd is into estate development operating around Madina and Adenta areas. Thecompany wants to know whether Monthly Income, Age and Educational level can be used todetermine House Size of their customers. As a Quantitative Analyst use the followingRegression output in the tables to answer the questions that follow:SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdjusted R. SquareStandard ErrorObservationsANOVARegressionResidualTotalInterceptAgeEducationLevelMonthlyIncome0.8640540.5945441.006797SSMSF14.9318 4.977266 4.9102861.01364135 5.068203820StandardErrorSignificanceF0.049566Lower95%Upper95%2.688690.000473 0.087385Coefficients1 Stat P-value-0.13123 1.096997 -0.11963 0.909436 -2.951150.043929 0.0169050.301484 -0.31237 0.767365 -0.86916 0.6808140.000771 0.000269 2.865152 0.035194 7.93E-05 0.001463 (iv)(v)(vi)(vii)Which of the independent variable(s) is/are significant in explaining the changes inHouse Sizes and why?If age changes by 1 unit, state the range of values within which House Size will fallfor 95% confidence level.Test the significance of Monthly income at 5% level. Interpret your results.Predict the Size of a House if Monthly Income of a customer of K3 Company Ltdincreases by Ghs500, Age by 2 years and Education level by 2 units.

There is a statistics summary output of a multiple regression model.Which is used to examine the…

Answered: SUMMARY OUTPUT Regression Statistics…

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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Minitab Source Factor Adj ss 0.047979 0.004451 DF Adj MS 0.015993 0.000032 F-Value 503.06 P-Value 3 0.000 Error Total 140 143 0.052430 2. Cola Weights For the four samples described in Exercise 1, the sample of regular Coke has a mean weight of 0.81682 lb, the sample of Diet Coke has a mean weight of 0.78479 lb, the sample of regular Pepsi has a mean weight of 0.82410 lb. and the sample of Diet Pepsi has a mean weight of 0.78386 lb. If we use analysis of variance and reach a conclusion to reject equal- ity of the four sample means, can we then conclude that any of the specific samples have means that are significantly different from the others? 3. Cola Weights For the analysis of variance test described in Exercise 1, is that test left-tailed, right-tailed, or two-tailed? 4. Cola Weights Identify the value of the test statistic in the display included with Exercise 1. In general, do larger test statistics result in larger P-values, smaller P-values, or P-values that are unrelated to…
Analysis 2 Table 1 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .752a .124 .109 2.781 Predictors: (Constant), Eating Style Table 2 ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 63.615 1 63.615 3.225 .006b Residual 448.568 58 7.734 Total 512.183 59 Dependent Variable: Stress Level Predictors: (Constant), Eating Style Table 3 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) 16.095 2.050 .352 7.852 .000 Eating Style .412 .144 2.868 .006 Dependent Variable: Stress Level A study was conducted to 60 students to identify their eating style and stress level during the period of movement control order (MCO) 3.0 in 2021. Researchers also identified the type of food preferred, gender and race…
Regression. A coach wants to see the relationship between the statistics of practice games and official games of a local soccer team. A sample of 24 players was used and the resulting (partial) Excel output is shown below. Assume both x and y form normal distributions. Regression Statistics Multiple R *** R Square 0.70524 Adjusted R Square 0.668395 Standard Error 8.703633 Observations 24 Coefficients Standard t Stat P-value Lower Upper 95% Error 95% Intercept 40.63461 8.506861 4.794266 0.001366 21.1673 60.40101 Midterm 0.718205 0.174917 4.379587 0.002365 0.362046 1.169078
what is the estimated regression equation.?
Explain these tables to me in detail
Solve its from frequency distribution and graphic presentations
X 0 1 2 3 4 P(x) 0.4 0.1 0.1 0.1 0.3 Please find the variance and round to one decimal place as needed.
What percentage of the variability in the number of delivery days for a car is NOT explained by knowing the number of factory options? SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations Intercept Factory Options 22.31% 72.16% 88.14% 77.69% O 4.64% 0.8814 0.7769 0.7216 4.6400 10 Coefficients 29.73333 3.284848 Standard Error 2.991435587 0.482113498
interpret the spss output below
The following data gives the number of employees at the bookstore and the number of minutes students wait in line to buy books at the beginning of the term. The independent variable is the number of employees and the dependent variable is the number of minutes. What is the y intercept? SSxx = 56.857; SS=2095.714; SSxy=-322.571 SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square X36899 0.96 0.93 0.91 y 67 54 47 33 31 25 12
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Using results from the regression model, discuss whether you would have confidence in this multiple regression model to predict expected salary based on GPA, age, and gender?

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SUMMARY OUTPUT Regression Statistics Multiple R R. Square Adjusted R Square Standard Error Observations 0.864054 0.594544 1.006797