An Academic Advisor Wants to Predict the Typical Starting Salary $$\hat { \beta } _ { 0 } = - 92040 \hat { \beta } 1 = 228 \mathrm {~s} = 3213 r ^ { 2 } = .66 r = .81 \mathrm { df } = 23 \quad t = 6.67$$

question 57

Multiple Choice

An academic advisor wants to predict the typical starting salary of a graduate at a top business school using the GMAT score of the school as a predictor variable. A simple linear regression of SALARY versus GMAT using 25 data points is shown below.
$$\hat { \beta } _ { 0 } = - 92040 \hat { \beta } 1 = 228 \mathrm {~s} = 3213 r ^ { 2 } = .66 r = .81 \mathrm { df } = 23 \quad t = 6.67$$
Give a practical interpretation of $r = .81$ .

• A) We estimate SALARY to increase \(81 \%\) for every 1-point increase in GMAT.
• B) We can predict SALARY correctly \(81 \%\) of the time using GMAT in a straight-line model.
• C) There appears to be a positive correlation between SALARY and GMAT.
• D) \(81 \%\) of the sample variation in SALARY can be explained by using GMAT in a straight-line model.

Understand the application and impact of the lower of cost or market rule on inventory valuation.

Appreciate the importance and challenges of assigning unit costs to inventory items in financial accounting.

Learn the relevance of net realizable value in inventory valuation for damaged and obsolete goods.

Analyze the reliability of inventory estimation methods and their significance for accounting and reporting.

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