Parameter estimatesDirect effectsFreedomGenerosityFamilyLife ExpectancyNote. Delta methodIndirect effectsFreedomFreedomGenerosityGenerosityFamilyFamilyTotal effectsFreedomGenerosityEstimate Std. ErrorFreedomGenerosityFamilyLife Expectancy1.4760.3811.1181.289GDP per CapitaHappiness ScoreHappiness ScoreGovernment CorruptionCDP per CapitaGovernment CorruptionGDP per CapitaGovernment CorruptionGDP per CapitaGovernment CorruptionHappiness ScoreHappiness ScoreLife ExpectancyHappiness ScoreHappiness ScoreLife ExpectancyNote. Delta method standard errors, normal theory confidence intervals, ML estimator.Happiness ScoreHappiness ScoreHappiness ScoreHappiness Scorestandard errors, normal theory confidence intervals, ML estimator.11110.3350.3220.1970.314Estimate Std. Error1.8280.2531.4022.278z-valueEstimate0.352-0.1280.2840.989Р4.409<.0011.183 0.2375.661 <.0014.102 <.001Happiness ScoreHappiness Score0.3310.3320.1940.227Estimatez-valueHappiness ScoreHappiness ScoreFamilyHappiness ScoreHappiness ScoreLife ExpectancyNote. Delta method standard errors, normal theory confidence intervals, ML estimator.Total indirect effects0.1190.233-0.2250.0970.298-0.0140.9350.054Р5.519<.0010.7610.4467.208 <.00110.035 <.001Std. Error z-value0.176 1.9950.150 -0.8570.1050.246Happiness ScoreHappiness ScoreHappiness ScoreHappiness ScoreNote. Delta method standard errors, normal theory confidence intervals, ML estimator.95% Confidence IntervalUpperLower0.820-0.2500.7310.673Std. Error0.0710.0960.0270.2480.0440.1050.1410.116 -1.9411.179-0.3982.1321.0111.5051.9051.0211.833z-value1.1291.65695% Confidence IntervalLowerUpper2.699 0.0074.014 <.0011.3583.097-0.4993.7701.2422.4770.9031.7832.72395% Confidence IntervalUpperLowerР0.0460.0060.392 -0.4220.0780.506РLower0.259-0.0870.098-0.0430.052-0.4520.174 -0.0430.0020.1090.618 -0.067<.0010.4490.214-0.03195% Confidence IntervalUpper0.6980.1650.4911.4720.3240.5090.0020.2370.4860.0401.4210.140 6. To further elaborate the regression model, the researchers of the research projectidentified that the factors can be categorized as psychosocial and political-economicfactors. The Psychosocial factors were the freedom, generosity, family and lifeexpectancy while the political-economic factors were GDP per Capita and GovernmentCorruption. To make sense of the factor distinctions, the researcher placed thepsychosocial factors as predictors while the political-economic factors as mediators,thereby, implementing a mediation analysis.A. Which among the political-economic factors can be considered significantmediators between psychosocial factors and happiness? Provide parameterestimates and p-values.B. Using the Total-Indirect Effects table, which among the psychosocial factors(predictors) have significant indirect effects towards happiness? Provide parameterestimates and p-values.C. Describe why the mediators significantly mediate the relationships in 6A. Provide atleast 2 research literature or articles per mediator.D. Based on your answer to 6B, why is the effect of the psychosocial factors of "indirectnature" towards happiness. Provide at least 2 research literature or articles per eachpredictor.

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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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indlude answer(s) for part(s) A, B, C & D.
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A psychological study aimed at predicting Al Ain secondary school students’ mental health scores via their scores in the life satisfaction scale. The researcher examines the following null hypothesis: there is no significant relationship between Al Ain secondary school students’ mental health and their life satisfaction scores at 0.05 level of significance. Use the following data to establish the required regression equation. Student # Mental health score out of 50 Life- satisfaction score out of 100 1 40 80 2 41 87 3 34 90 4 30 78 5 44 89 6 42 85 7 45 88 8 32 77 9 47 90 10 22 57 11 30 78 12 28 77 13 35 76 14 40 84 15 31 76 16 39 80 17 41 84 18 24 60 19 22 50 20 37 75 21 40 80 22 38 78 23 29 60 24 24 55 25 24 62 26 29 61 27 32 65 28 34 66 29 28 67…
a. Develop the least squares estimated regression equation that relates labor hours to house square footage and type of flooring. b. Use the regression equation developed in part (a) to predict labor hours when the house size is 3350 square feet and the type of flooring is wood.
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