A number of Linear Regression1 Relationship Between Eighth Grade IQ, Eighth Grade Summary Reasoning and Ninthgrade Math Rating For a statistics class challenge, college students examined the connection between x 1 = 8thgrade IQ, x2 = eighth grade Summary Reasoning and y = ninth grade math scores for 20 college students. The information aredisplayed under.Pupil1234567891011121314151617181920Math Rating3331353841373739434041444045484531474348IQ95100100102103105106106106109110110111112112114114115117118Summary Reas2824293033323436383940434142464441474249Open the dataset IQ discovered within the Datasets folder in ANGEL. Carry out a linear regression with theResponse (dependent variable) math rating and the variables IQ and Abstract_Reas because the Predictors(impartial variables). Retailer/Save the (unstandardized) Residuals and Fitted(Predicted) values.The output ought to look as follows:MINITAB: Regression Evaluation: Math Rating versus IQ, Abstract_ReasThe regression equation isMath Rating = 54.1 – Zero.484 IQ + 1.02 Abstract_ReasPredictorConstantIQAbstract_ReasS = three.00271Coef54.05-Zero.48361.0185SE Coef22.990.29550.2656R-Sq = 70.5percentT2.35-1.643.84P0.0310.1200.001R-Sq(adj) = 67.1percentAnalysis of VarianceSourceRegressionDF2SS366.92MS183.46F20.35P0.0001Residual ErrorTotal1719153.28520.209.02SPSS: Regression Evaluation: Math Rating versus IQ, Abstract_ReasModel SummarybModelRR Sq..840aStd. Error of theSquare1Adjusted REstimate.705.6713.003a. Predictors: (Fixed), Abstract_Reas, IQb. Dependent Variable: MathScoreANOVAaModelSum of SquaresdfMean SquareRegression2183.462Residual153.27617520.200Sig..000b9.016Complete1366.924F20.34819a. Dependent Variable: MathScoreb. Predictors: (Fixed), Abstract_Reas, IQCoefficientsaModelUnstandardized CoefficientsStandardizedtSig.CoefficientsB(Fixed)Std. Error22.991IQ-.484.296Abstract_Reas154.0531.019.266Beta2.351.031-.573-1.636.1201.3433.835.001a. Dependent Variable: MathScorea. What’s the regression equation and supply an interpretation of every slope by way of the change in Yper unit change in X?b. Create two scatter plots of the measurements by choosing math rating because the response (y-axis), IQ andabstract reasoning because the predictors (x-axis) Describe the connection between math rating and IQ andmath rating and summary reasoning.c. Based mostly on the output, what’s the take a look at of the slopes for this regression equation? That’s, present the nulland different hypotheses, the take a look at statistic, p-value of the take a look at, and state your resolution and conclusion.2nd. From the output, what’s the which means of the ANOVA F-test? Present the 2 hypotheses (Ho and Ha)statements, resolution and conclusion.e. Verify assumptions of fixed variance (a scatterplot of the residuals versus the suits(predicted) values)and normality (Minitab a chance plot or SPSS a Q-Q plot in SPSS). What are your conclusionsbased on these graphs?MINITAB: Scatterplot by Graph > Scatter Plot > Easy. Likelihood plot by Graph > ProbabilityPlot > SingleSPSS Customers: Scatterplot by Graphs > Legacy Dialogues > Scatter/Dot > Easy Scatter Q-Q plot byAnalyze > Descriptive Statistics > Discover and enter Unstandardized Residuals in Dependent Listclick Plots and choose field for Regular plots with exams
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