Statistics: Analysis of Variance (ANOVA) – #74


Question: Height is frequently named as a good predictor variable for weight among people of the same age and gender. The following are the raw data and results of a regression analysis of the heights and weights of a sample of 14 males between the ages of 19 and 26 who participated in a study.

HEIGHT (cm) WEIGHT (kgs)
185 83.9
180 99.0
173 63.8
168 71.3
175 65.3
183 79.6
184 70.3
174 69.2
164 56.4
169 66.2
205 88.7
161 59.7
177 64.6
174 78.8
Variables Entered/Removed(b)
Model Variables Entered Variables Removed Method
1 HEIGHT(a) . Enter
a All requested variables entered.
b Dependent Variable: WEIGHT
Model Summary(b)
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .689(a) .475 .432 9.00512
a Predictors: (Constant), HEIGHT
b Dependent Variable: WEIGHT
ANOVA(b)
Model Sum of Squares df Mean Square F Sig.
1 Regression 881.262 1 881.262 10.867 .006(a)
Residual 973.106 12 81.092
Total 1854.369 13
a Predictors: (Constant), HEIGHT
b Dependent Variable: WEIGHT
Coefficients(a)
Unstandardized Coefficients Standardized Coefficients t Sig.
Model B Std. Error Beta

1 (Constant) -60.622 40.492 -1.497 .160
HEIGHT .755 .229 .689 3.297 .006
a Dependent Variable: WEIGHT

What information do you look at in the output to determine whether there is a statistically significant relationship between height and weight in this sample?

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