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2.1.1 Relationship between Age and Weight. Model Summary Table Conduct simple li

ID: 3226090 • Letter: 2

Question

2.1.1 Relationship between Age and Weight. Model Summary Table

Conduct simple linear regression for age and weight.

Looking at the Model Summary table:

What is the value of R? …………..

What does this tell us about the association between weight and age?

What is the value of R Square? …………..

What does this tell us about the model including age as a predictor of weight?

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.039a

.002

.000

12.287

a. Predictors: (Constant), weight in kgs

Relationship between age and weight – Anova Table

Looking at the ANOVA

What is the value of the F-Ratio? …………..

What are your conclusions about the model based on this table?

ANOVAa

Model

Sum of Squares

df

Mean Square

F

Sig.

1

Regression

168.410

1

168.410

1.116

.291b

Residual

110355.486

731

150.965

Total

110523.896

732

a. Dependent Variable: age

b. Predictors: (Constant), weight in kgs

2.1.2 Relationship between Sex and Weight

Now repeat the simple regression for sex and weight:

Looking at the Model Summary table:

What is the value of R? …………..

What does this tell us about the association between weight and sex?

What is the value of R Square? …………..

What does this tell us about the model including sex as a predictor of weight?

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.496a

.246

.245

.412

a. Predictors: (Constant), weight in kgs

Looking at the Model Summary table:

What is the value of R? …………..

What does this tell us about the association between weight and age?

What is the value of R Square? …………..

What does this tell us about the model including age as a predictor of weight?

Explanation / Answer

value of R =0.039

this tells us that there is no association between weight and age as R value is very less

value of R Square =0.002

this tells us that 0.2% variation in age is explained by weight.

2)value of the F-Ratio =1.116

conclusions: as p value is greater then 0.05 level, we can not reject null hypothesis; that there is no correlation between age and weight

3)value of R =0.496

this tells us that there is moderate association between weight and age as R value is in b/w of 0 and 1

value of R Square =0.246

this tells us that 24.6 % of variation in gender is explained by weight