Interpret the assocfation between agea nd math scores in the univariate regression model, and is the association between them significant?How much variance in math score is explained by age in the univariate regression model? DataHOExploration T-Tests> Model BuilderAnalysesLinear RegressionFit MeasuresRR²Adjusted R²юн88ANOVA Regression Frequencies> Reference Levels> Assumption ChecksModel FitHOHючFactorsFactorOverall Model TestF test→→jamovi - SAT FroDisLinear RegressionModel Fit Measures1ModelRR²0.215 0.0463Omnibus ANOVA TestSum of SquaresAge3088Residuals63607Note. Type 3 sum of squaresModel Coefficients - MathPredictor EstimateIntercept 402.04Age6.92SE142.31dfF0.874118tOverall Model Testdf1df21Mean Square308835342.8257.40 0.935Р0.0110.36218F0.874P0.3620.215P0.362Stand. Estimate[3]

The regression model shows the relationship b/w 1 dependent variable and 1 or more independent…

Interpret the assocfation between agea nd math scores in the univariate regression model, and is the association between them significant? How much variance in math score is explained by age in the univariate regression model?

Interpret the assocfation between agea nd math scores in the univariate regression model, and is the association between them significant? How much variance in math score is explained by age in the univariate regression model?

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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Question

Interpret the assocfation between agea nd math scores in the univariate regression model, and is the association between them significant?

How much variance in math score is explained by age in the univariate regression model?

Data
HO
Exploration T-Tests
> Model Builder
Analyses
Linear Regression
Fit Measures
R
R²
Adjusted R²
юн
88
ANOVA Regression Frequencies
> Reference Levels
> Assumption Checks
Model Fit
HOH
юч
Factors
Factor
Overall Model Test
F test
→→
jamovi - SAT FroDis
Linear Regression
Model Fit Measures
1
Model
R
R²
0.215 0.0463
Omnibus ANOVA Test
Sum of Squares
Age
3088
Residuals
63607
Note. Type 3 sum of squares
Model Coefficients - Math
Predictor Estimate
Intercept 402.04
Age
6.92
SE
142.31
df
F
0.874
1
18
t
Overall Model Test
df1
df2
1
Mean Square
3088
3534
2.825
7.40 0.935
Р
0.011
0.362
18
F
0.874
P
0.362
0.215
P
0.362
Stand. Estimate
[3]

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