Thirty employed single individuals were randomly selected to examine the relationship between their age (Age) and their credit card debt (Debt) expressed as a percentage of their annual income. Three polynomial models were applied and the following table summarizes Excel's regression results. If you impose the restrictions β₂ = β₃ = 0 on the model Debt = β₀ + β₁Age + β₂Age²^{+ β}₃Age³+ ε, what will be the sum of the squared errors (SSE_R) computed for the restricted model?

Question

Thirty employed single individuals were randomly selected to examine the relationship between their age (Age) and their credit card debt (Debt) expressed as a percentage of their annual income. Three polynomial models were applied and the following table summarizes Excel's regression results.

If you impose the restrictions β₂ = β₃ = 0 on the model Debt = β₀ + β₁Age + β₂Age²^{+ β}₃Age³+ ε, what will be the sum of the squared errors (SSE_R) computed for the restricted model?

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The Answer of Thirty employed single individuals were randomly selected to examine the relationship between their age (Age) and their credit card debt (Debt) expressed as a percentage of their annual income. Three polynomial models were applied and the following table summarizes Excel's regression results. If you impose the restrictions β₂ = β₃ = 0 on the model Debt = β₀ + β₁Age + β₂Age²^{+ β}₃Age³+ ε, what will be the sum of the squared errors (SSE_R) computed for the restricted model?

Thirty Employed Single Individuals Were Randomly Selected to Examine the Relationship