In the Chapter 16 data set, you will find scores on three variables. The outcome
ID: 3174939 • Letter: I
Question
In the Chapter 16 data set, you will find scores on three variables. The outcome variable is overall health (labeled as “health”) with higher scores indicating higher levels of overall health. The predictor variables are preference for sweets (labeled as “sweets”) with higher scores indicating higher levels of preference for sweets. Gender with 1 indicating male and 2 indicating female, and body mass index (labeled as BMI) with higher numbers indicate greater obesity. Using a regression analysis find out how well the predictor variables predict overall health.
Include a paragraph explaining your results.
Regression Data Set2 C: Users Jessica Downloads Chapter+16+Data Set. sav Variables Entered/Removeda Variables Variables Removed Gender, BMI, Sweets a. Dependent Variable: Health b. All requested variables entered. Model Summary Adjusted R Std. Error of the R Square Square .885 .784 743 9.483 a. Predictors: (Constant), Gender, BMI, Sweets ANOVA Sum of Squares Mean Square Regression 5217.969 3 1739.323 19.340 .000 1438.981 89.936 Residual 6656.950 a. Dependent Variable: Health b, Predictors: (Constant), Gender, BMI, Sweets Coefficients Standardized Unstandardized Coefficients Coefficients Std. Error Beta Sig Model (Constant) 17.884 9.495 169.813 1.402 Sweets -2.635 4.309 -9.616 a. Dependent Variable: Health GGraph Page 1Explanation / Answer
1.
We are regressing 3 variables Gender, BMI and Sweets with overall health
2.
We get R2 of .743 meaning 74.3% of variance in Overall Health is explained by the 3 variables. The correlation coefficient is .865
3.
The regression equation is significant ( it' p value being less than .05)
4.
The coefficeint table show which variables are actually significant. So, all are significant, given an alpha = .05.
The equation is OverallHealth = 169.813-3.094Sweets-2.635BMI -9.616Gender