**PLEASE READ THE FOLLOWING BEFORE PROCEEDING:**

This is only a tool. In no way does this tool predict certainty. There are many variables that may have an influence and cannot be captured within this snapshot view of predicting college-going GPA. Please use this as a tool to better inform you of your likely success.

Variables used and coefficients: R2 = .4458

**Explaining The High School Coefficient**

A student’s high school is measured by the Composite ACT test scores, then placed in quartiles where 1 is the most favorable and 4 being least favorable, then multiplied by the quartile. Ex. HS=1 x (0.06514) Total = (.065)

• High School: Low End Estimate: (0.06514), Middle: (0.05987), Upper Estimate: (0.05459)

• Brackets [] indicate number to be subtracted.

**Explaining The English and Math Coefficients**

The amount of English and mathematics courses a student took in high school was determined to be an important factor when determining college-going GPA. Each number of math and English courses are multiplied by the coefficient.

• English: Low End Estimate: 0.01512, Middle: 0.03148, Upper Estimate: 0.04784

• Math: Low End Estimate: 0.01297, Middle: 0.01881, Upper Estimate: 0.02465

**Explaining The High School GPA Coefficient**

High School GPA: the students high school grade point average. This was the most determining factor when predicting college-going GPA. HSGPA x Coefficient.

• HS GPA: Low End Estimate: 0.43066, Middle: 0.44869, Upper Estimate: 0.46673

**Explaining The ACT Composite Coefficient**

ACT Composite Score: Since the majority of Tennessee students take the ACT, data has supported making this a strong category. For the purposes of this model, ACT and HS GPA are multiplied and applied to the following coefficients: EX. HSGPA = 3.0 and ACT Comp=25, Total = 75

• ACT Composite: Low End Estimate: 0.00995, Middle: 0.01044, Upper Estimate: 0.01093

**Explaining The Income Coefficient**

Parents/Independent Income: Income has been determined to have an affect on college-going GPA. Income is broken into ten categories and assigned a variable, 0-9. That variable is multiplied by the coefficient.

• Income: Low End Estimate: 0.00572, Middle: 0.00754, Upper Estimate: 0.00935

**Explaining The Total Hours/Remedial Hours Coefficient**

Total Hours/Remedial Hours: These two fields are really combined into one coefficient, which looks at % college credit hours. ((Remedial Hours / Total Hours) * 100) = % College credit hours

• Hours: Low End Estimate: [0.00347], Middle: [0.00301], Upper Estimate: [0.00255]

**Explaining The Science/Math Coefficient**

Science/Math: Generally, science and mathematics courses are more difficult curriculums, which this parameter factors in. Boolean value assigned for yes/no answer.

• Science/Math: Low End Estimate: [0.14180], Middle: [0.13313], Upper Estimate: [0.11817]

**Explaining The Institution Coefficient**

Institution: Institutions have varying standards of admission. Institutions in the model were assigned the standard of Open, Less Selective, Selective and More Selective. Depending on the institution, a Boolean valued is assigned and multiplied by the following coefficients:

• If Considered Open: Low End Estimate: 0.09102, Middle: 0.10438, Upper Estimate: 0.11774, then multiplied by 1 (all other values assigned 0)

• If Considered Less Selective: Low End Estimate: 0.15820, Middle: 0.18942, Upper Estimate: 0.22064, then multiplied by 1 (all other values assigned 0)

• If Considered More Selective: Low End Estimate: [0.16918], Middle: [0.15477], Upper Estimate: [0.14036] then multiplied by 1 (all other values assigned 0)

• If Considered Selective: All values assigned 0 boolean value