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

question 45

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. $$\hat { \beta } _ { 0 } = - 92040 \hat { \beta } 1 = 228 s = 3213 r ^ { 2 } = .66 r = .81 \mathrm { df } = 23 \quad t = 6.67$$
Give a practical interpretation of $r = .81$ .

• A) \(81 \%\) of the sample variation in SALARY can be explained by using GMAT in a straight-line model.
• 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) We estimate SALARY to increase \(81 \%\) for every 1 -point increase in GMAT.

Recognize the role of membranes in cellular function, including exchange of materials and waste.

Understand the principles of cell theory.

Discuss the implications of cell biology on our understanding of life.

Understand the use of various microscopy techniques for studying cellular structures.

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