Statistical Analysis of Regression Model for DDT Prediction
School
Virginia Commonwealth University**We aren't endorsed by this school
Course
STAT 441
Subject
Economics
Date
Dec 11, 2024
Pages
2
Uploaded by PrivateIceEmu11
1. Question 3: Is the overall model statistically useful for predicting y ?- Hypothesis Test:- ( H_0): All the beta coefficients are equal to zero (the model is not useful).- ( H_1): At least one of the beta coefficients is not equal to zero (the model is useful).- P-value: 0.1345 (greater than 0.05).- Conclusion: Fail to reject (H_0). There is insufficient evidence to suggest that the regressionequation is statistically significant. Hence, the model is not statistically useful for predicting y.2. Question 4: Interpretation of R^2 and Standard Error (SE):●R^2 = 0.039: Indicates that only 3.9% of the variability in DDT is explained by theindependent variables (length, weight, miles). This is very low, suggesting a poor modelfit.●Standard Error (SE = 97.4756): This value represents the standard deviation of theresiduals. A high SE indicates that the observed values are widely scattered around thepredicted regression line, further emphasizing the model's lack of precision.Question 5: Evaluating the significance of predictors:●Length:○P-value = 0.02 (less than 0.05).○Conclusion: Length is a statistically significant predictor of DDT. An increase inlength is associated with an increase in DDT levels.●Weight and Miles:
○These predictors are not explicitly analyzed for their individual p-values here.Assuming their p-values are greater than 0.05, they would not be consideredsignificant predictors.Question 6: Prediction of DDT Level:●Given values:○Length = 40, Weight = 800 g, Miles = 100.●Regression equation:DDT=−108.07+3.77(Length)−0.05(Weight)+0.09(Miles)●Substituting the values:DDT=−108.07+3.77(40)−0.05(800)+0.09(100)DDT=−108.07+150.8−40+9=11.73Predicted DDT Level: 11.73.