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SCENARIO 17-11 A Logistic Regression Model Was Estimated in Order to Predict

question 43

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SCENARIO 17-11
A logistic regression model was estimated in order to predict the probability that a randomly chosen
university or college would be a private university using information on mean total Scholastic
Aptitude Test score (SAT) at the university or college, the room and board expense measured in
thousands of dollars (Room/Brd), and whether the TOEFL criterion is at least 550 (Toefl550 = 1 if
yes, 0 otherwise.) The dependent variable, Y, is school type (Type = 1 if private and 0 otherwise).
The Minitab output is given below: SCENARIO 17-11 A logistic regression model was estimated in order to predict the probability that a randomly chosen university or college would be a private university using information on mean total Scholastic Aptitude Test score (SAT) at the university or college, the room and board expense measured in thousands of dollars (Room/Brd), and whether the TOEFL criterion is at least 550 (Toefl550 = 1 if yes, 0 otherwise.) The dependent variable, Y, is school type (Type = 1 if private and 0 otherwise). The Minitab output is given below:   -Referring to Scenario 17-11, there is not enough evidence to conclude that the model is not a good-fitting model at a 0.05 level of significance.
-Referring to Scenario 17-11, there is not enough evidence to conclude that the
model is not a good-fitting model at a 0.05 level of significance.


Definitions:

Income Statement

A financial statement that reports a company's revenues, expenses, and net income over a specific period, showing profitability.

Special Item

Unusual or infrequent gains or losses not classified as extraordinary but significantly important to understand a company's financial health.

Asset Increase

An increase in the total value of assets owned by a company, which can occur due to acquisitions, improvements, or valuation increases.

Corresponding Decrease

A decrease in one variable or metric that occurs in response to an increase in another variable.

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