Predictive Model for the Repayment of Student Loans in Community Colleges.
Predictive Model for the Repayment of Student Loans in Community Colleges.
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Because the order of inclusion in the formula is different and the mathemati- cal weighting is improved, the accuracy of the formula is improved.
Based on the results of the discriminant analysis, it would appear that the best predictive formula for determin- ing correct classification of defaulting and non-defaulting community college students would include only data regarding the students' loan totals and marital status. Adding the 73 variables grade point average, sex, college standing and a...ge, essentially maintained the effectiveness of the pre- diction formula. As evidenced, the stepwise technique em- ployed to produce the second and third formulae improved the accuracy for categorical classification over the regular multiple discriminant analysis technique utilized for the first formula.
Results Based on chance alone, one would expect to predict correctly the proper placement of students into the two categories (defaulting and non-defaulting) 50% of the time.
The prediction formula generated by the inclusion of data concerning loan total and marital status increases the like- lihood of making an accurate prediction from 50% to 71%.
What to read after Predictive Model for the Repayment of Student Loans in Community Colleges.?
You can find similar books in the "Read Also" column, or choose other free books by Schmidt, James A., 1950- to read onlineMoreLess
To quickly assess the difficulty of the text, read a short excerpt:
Because the order of inclusion in the formula is different and the mathemati- cal weighting is improved, the accuracy of the formula is improved.
Based on the results of the discriminant analysis, it would appear that the best predictive formula for determin- ing correct classification of defaulting and non-defaulting community college students would include only data regarding the students' loan totals and marital status. Adding the 73 variables grade point average, sex, college standing and a...ge, essentially maintained the effectiveness of the pre- diction formula. As evidenced, the stepwise technique em- ployed to produce the second and third formulae improved the accuracy for categorical classification over the regular multiple discriminant analysis technique utilized for the first formula.
Results Based on chance alone, one would expect to predict correctly the proper placement of students into the two categories (defaulting and non-defaulting) 50% of the time.
The prediction formula generated by the inclusion of data concerning loan total and marital status increases the like- lihood of making an accurate prediction from 50% to 71%.
What to read after Predictive Model for the Repayment of Student Loans in Community Colleges.?
You can find similar books in the "Read Also" column, or choose other free books by Schmidt, James A., 1950- to read onlineMoreLess
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