18. Conduct a full hypothesis test for the presence of a linear relationship. In
ID: 2935981 • Letter: 1
Question
18. Conduct a full hypothesis test for the presence of a linear relationship. Interpret your results.19. Write the full linear regression equation.
20. Which is a better predictor of the ideal number of children an individual would like to have, the mean of the variable ideal number of children or the linear regression equation?
20. Which is a better predictor of the ideal number of children an individual would like to have, the mean of the variable ideal number of children or the linear regression equation?
Model Summary Adjusted Std. Error of Model 013a 001 1.574 a. Predictors: (Constant), Hours Per Day Watching TV ANOVA Sum of Model df Si 412 2.477 Regression 412 166 683 Residual2375.494 Total 959 960 2375.906 a. Predictors: (Constant), Hours Per Day Watching TV b. Dependent Variable: Ideal Number of Children Coefficients Unstandardized Standardized Coefficients Coefficients Model B Std. ErrorBeta 2.789 081 .009 34.315 Constant) Hours Per Day Watching TV 013 408 .022 683 a Dependent Variable: Ideal Number of Children 18. Conduct a full hypothesis test for the presence of a linear relationship. Interpret your results. 19. Write the full linear regression equation. 20. Which is a better predictor of the ideal number of children an individual would like to have, the mean of the variable ideal number of children or the linear regression equation?
Explanation / Answer
Solution-
18. Null hypothesis- no linear model exists
Alternative hypothesis- linear model exists
No as we see from the above summary table , f-value test statistic = .166 and concerned p-value is .683
As p-value is greater than .05 thus null hypothesis is not rejected at 5% level of significance.
Thus No linear relationship exists.
19. Linear regression equation is-
Y = 2.789 - .009 * X
Where Y = Hours per day watching TV and X = Ideal number of children
20. Mean number of ideal number of children would be a better indicator as linear regresssion model is a poor fit here as visible from R2 value too.
Please rate this!
TY!
Related Questions
drjack9650@gmail.com
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.