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We need to investigate whether age, sex and height are associated with weight be

ID: 3229080 • Letter: W

Question

We need to investigate whether age, sex and height are associated with weight before proceeding with the multivariate regression.

Looking at the Model Summary table:

What is the value of R? 0.039

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

What is the value of R Square? 0.002

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

Relationship between age and weight – Anova Table

Sig. Value from ANOVA table = 0.291

Looking at the ANOVA

What is the value of the F-Ratio? 1.116

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

Now repeat the simple regression for sex and weight:

Looking at the Model Summary table:

What is the value of R? 0.496

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

What is the value of R Square? 0.246

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

Sig. Value from ANOVA table = 0.000

Looking at the ANOVA

What is the value of the F-Ratio? 239.646

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

Looking at the Model Summary table:

What is the value of R? 0.039

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

What is the value of R Square? 0.002

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

Explanation / Answer

From Model Summary table:

1) R value=0.039, it tells that there is 3.9% relation association between variables weight and age

2) R Square = 0.002, it explains only 0.2% variability of response data around mean

3)Siginificant value from anova table = 0.291 and F= 1.116

Comparing siginificant value 0.291 and level of significance 0.05, significant value is greater than leel of significance

Conclusion: we can accept null hypothesis

Simple regression for sex and weight:

1) R value=0.496, it tells that there is 49.6% relation association between variables weight and sex

2) R Square = 0.246, it explains only 24.6% variability of response data around mean

3)Siginificant value from anova table =0.000 and F= 239.646

Comparing siginificant value 0.000 and level of significance 0.05, significant value is lesser than level of significance

Conclusion: we can reject null hypothesis

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