Using General Linear Test 2. Use the output below to assess whether the Quetelet index (QUET =100*weight/height²) is useful in the model.Analysis of VarianceSourceDFSeq SS Adj SS Adj MSRegression 4 5054.95 5054.95 1263.74 24.8873 0.0000001 3861.63 737.23 737.23 14.5186 0.000729AGESMK1QUET1QUET *QUET 1ErrorTotal2731FP828.05 568.24 568.24 11.1905 0.0024260.1464680.082513200.14 113.52 113.52165.13 165.13 165.131371.02 1371.026425.9750.782.23553.2519

2. We have to identify whether the Quetelet index is useful in the model.

Answered: 2. Use the output below to assess…

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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Quastion 6 Research has shown that ofese adult males have lower level's of festasterone Howeyer t is unknown whether this same patern occurs in adolescents A study was'conducte that measusedthe testasterond (in nmol/ Itres in fwo independent, iandom Sample's The furst samp le included 1o obese a dolescents. Testosterone levels Healthy Waight Obese Adolescents- (n=D10) 0.16 0:30 0311060020 Adolesdents 0.04 036 010 031 0.19 0-940-10 0.60 0.F3 0-941 b39| Mean- 0.2550 Variana=0.0061 Mean =0-5483 Vanance 0.1389 a) based on thLs sgmple information does it appearthat the pop ulation vananas, are equal 'r unequal.? txplain. 5)1s there a sgnificant dffecence in the arerage testpstenonelevels befween obese and tealthy,Weigt adolescents: To answer this Conduct an appropnate bypothesis test using the,P-value method and a nufıçant lulelof 540.What can you CONJ lude about these two, qroups of adobat OWhat assumytion must be true for the result in Porf (b) to be vellid.
Regression
Pls show ur work thank u
Data/565-Hypothesis testing for comparing population means uses the difference (x1 - x2) where the samples are assumed to be taken from populations with a distribution.
Can you please check my work
Residuals in a regression model: (pick one or more) * A) Represent the differences between observed values and values predicted by a regression model * B) smaller (in absolute value) in a poorly fitted compared to a fitted model * C) Contribute to the calculation of an F test statistic
Correlation Be able to complete an ANOVA table for regression SSregression model SSresidual/error What is R squared?
Regression analysis
Moddel Parameters (Points) Source Value Standard Error t Pr > |t| Intercept 0.437798 5.9182 0.073948 0.9428 Hours 0.829539 0.109474 7.57748 0.0001 Analysis of Variance (Points) Source Sum of Squares Df Mean Square F Pr > |t| Model 3249.72 1 3249.72 57.42 0.0001 Error 452.779 8 56.5974 Corrected Total 3702.5 9 1. Use the estimatedd regression to predict the points of a student who spent 50 hours studying for this course. A. Y=50, so Y^=50 B. X=50, so Y^=0.83+0.44(50)=22.83 C. X=50, so Y^=0.44+0.83(50)=41.94 D. Unable to find. 1a. If a student spennt 120 hours studying for this course, would you feeel comfortable to use your estimated regresssion equation to predict his points? Why? A. The range of X in our data is from 10 to 85. X = 120 is outside the range of X. I do not feel comfortable to use my estimated regression equation to predict his points as the linear relationship may not hold when X = 120. B. I know that 120 hours is…
What is a residual for a multiple regression model and the data that is used to create it? Select one. A statistic that is used to evaluate the significance of the multiple regression model A statistic that explains the relationship between response and predictor variables The predicted value of the response variable using the multiple regression model The difference between the actual value of the response variable and the corresponding predicted value (regression error) using the multiple regression model
Interperting Regression Results (Continuation of Exercise 8-39) The following table showsadditional regression results presented by the researchers in the study described in Exercise 8-39.There are two regressions. The right-hand column shows the results for all patients, including thosetreated with laparoscopic surgery. The left-hand column shows the results for the sample of patientswho were treated without the laparoscopic surgery.Nonlaparoscopic Patients Only All PatientsCoefficients for Independent VariablesRegression intercept $8,043 $3,719 Length of stay Coefficient* Not significant 861 Standard error for the coefficient Not applicable 80 Number of complications Coefficient 3,393 1,986 Standard error for the coefficient 1,239 406 Laparascopic Coefficient Not applicable 908 Standard error for the coefficient Not applicable 358 R-squared 0.11 0.53 *All independent variables are significant at the level of p = .05 (and t-value >2) except for the length of stay variable in the…
Numericall method

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