Referencing the values in the multiple regression analysis,Reading ability is the independent variable age and IQ are the dependent variables 1. Does age and IQ predict the reading ability?2. Which of the predictors(age or IQ) is the stronger predictor of reading ability? What evidence helps support your answer? CorrelationsCorrelationsageIQreading abilityagePearson Correlation1-.198.846Sig. (2-tailed).402.000N202020IQPearson Correlation-.1981.150Sig. (2-tailed).402.527202020reading abilityPearson Correlation.846.1501Sig. (2-tailed).000.527202020**. Correlation is significant at the 0.01 level (2-tailed). Model SummaryAdjusted RSquareStd. Error ofModelRR Squarethe Estimate1.906.821.800.30739a. Predictors: (Constant), IQ, ageANOVASum ofModelSquaresdfMean SquareFSig.1Regression7.37423.68739.018.000Residual1.60617.094Total8.98019a. Dependent Variable: reading abilityb. Predictors: (Constant), IQ, ageaCoefficientsStandardizedUnstandardized CoefficientsCoefficientsModelВStd. ErrorBetaSig.1(Constant)-.7031.247-.564.580age.584.067.9128.711.000IQ.036.011.3313.165.006a. Dependent Variable: reading ability

Multiple regression analysis is used to determine the significant relation between more than two…

Referencing the values in the multiple regression analysis, Reading ability is the independent variable age and IQ are the dependent variables 1. Does age and IQ predict the reading ability? 2. Which of the predictors(age or IQ) is the stronger predictor of reading ability? What evidence helps support your answer?

Referencing the values in the multiple regression analysis, Reading ability is the independent variable age and IQ are the dependent variables 1. Does age and IQ predict the reading ability? 2. Which of the predictors(age or IQ) is the stronger predictor of reading ability? What evidence helps support your answer?

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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What is the relationship between the number of minutes per day a woman spends talking on the phone and the woman's weight? The time on the phone and weight for 8 women are shown in the table below. Time 46 60 43 39 18 20 35 18 Pounds 138 142 135 116 119 98 125 112 r2r2 = (Round to two decimal places) Interpret r2r2 : There is a 71% chance that the regression line will be a good predictor for women's weight based on their time spent on the phone. Given any group of women who all weight the same amount, 71% of all of these women will weigh the predicted amount. There is a large variation in women's weight, but if you only look at women with a fixed weight, this variation on average is reduced by 71%. 71% of all women will have the average weight. The equation of the linear regression line is: ˆyy^ = + xx (Please show your answers to two decimal places)
c) The store owner lets you know they are introducing a new bike. Using your model above what is your prediction for the price of the new bike if the bike weighs 17 pounds and is American Made.
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The correct answer is option C but I do not know how to find the number that go inside it.