Question

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 and whether the TOEFL criterion is at least 90 (Toefl90 = 1 if yes, 0 otherwise). The dependent variable, Y, is school type (Type = 1 if private and 0 otherwise). The PHStat output is given below: Binary Logistic Regression Predictor Coefficients SE Coef Z p-Value Intercept -3.9594 1.6741 -2.3650 0.0180 SAT 0.0028 0.0011 2.5459 0.0109 Toefl90:1 0.1928 0.5827 0.3309 0.7407 Deviance 101.9826 True or False: The null hypothesis that the model is a good-fitting model cannot be rejected when allowing for a 5% probability of making a type I error. True False

          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 and whether the TOEFL criterion is at least 90 (Toefl90 = 1 if yes, 0 otherwise). The dependent variable, Y, is school type (Type = 1 if private and 0 otherwise).

The PHStat output is given below:

Binary Logistic Regression
Predictor Coefficients SE Coef Z p-Value
Intercept -3.9594 1.6741 -2.3650 0.0180
SAT 0.0028 0.0011 2.5459 0.0109
Toefl90:1 0.1928 0.5827 0.3309 0.7407
Deviance 101.9826

True or False: The null hypothesis that the model is a good-fitting model cannot be rejected when allowing for a 5% probability of making a type I error.

True
False

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 and whether the TOEFL criterion is at least 90 (Toefl90 = 1 if yes, 0 otherwise). The dependent variable, Y, is school type (Type = 1 if private and 0 otherwise).

The PHStat output is given below:

Binary Logistic Regression
Predictor Coefficients SE Coef Z p-Value
Intercept -3.9594 1.6741 -2.3650 0.0180
SAT 0.0028 0.0011 2.5459 0.0109
Toefl90:1 0.1928 0.5827 0.3309 0.7407
Deviance 101.9826

True or False: The null hypothesis that the model is a good-fitting model cannot be rejected when allowing for a 5% probability of making a type I error.

True
False

Added by Barbara B.

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