In a regression equation, the evaluation criteria examine the significance of _________?
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Answer: A. independent variable
Explanation
Evaluation criteria in a regression equation test whether the independent variables are statistically significant in explaining the dependent variable. Analysts examine p-values and t-statistics to determine if an independent variable has a genuine impact. Insignificant independent variables indicate that the chosen driver may not reliably predict cost behavior. Regression equations model total costs using independent activity drivers and estimated parameters. Statistical significance testing helps determine whether relationship coefficients differ significantly from zero. Standard evaluation criteria include economic plausibility, goodness of fit, and coefficient significance.
Financial modelers evaluate regression equations to ensure they select only meaningful predictors for budgets. Including statistically insignificant variables in cost formulas degrades the predictive accuracy of the model. Management relies on significant regression drivers to forecast expenses and control operational activities. Option A is correct because regression evaluation criteria specifically examine independent variable significance. Dependent variable represents the cost being predicted rather than the predictor parameters being tested. Significance plotting is a colloquial description and not the formal statistical term used for parameter evaluation.
- Subject
- Accounting and Finance
- Category
- Accounting
- Topic
- —
- Difficulty
- medium
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