Practical Statistics Regression. There are six statistics that will answer 90% of all questions! 1. Descriptive 2. Chi-square 3. Z-tests 4. Comparison.

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Presentation transcript:

Practical Statistics Regression

There are six statistics that will answer 90% of all questions! 1. Descriptive 2. Chi-square 3. Z-tests 4. Comparison of Means 5. Correlation 6. Regression

Regression tests the degree of association between interval and ratio measures, AND gives the best fit to the data.

Regression Does three things: 1. Association 2. Best fit 3. Prediction

Regression Regression creates an equation: A simple linear equation would be: Y = bX + a

Remember the correlations from the last lesson…. Can we use the correlations to create equations to estimate one variable from another?

For example: Evaluations = b*Personality + a Y = bX + a

So… Evaluation = * Personality

An example can be found here:

The equations do not have to be linear?

Regression can use more than one variable to predict. This is called multiple regression.

Evaluation = * Personality * ExpGrd – * FinalGrd – 0.809

Some other examples can be found here:

Question: What is the final grade in a class related to? Question: Is the final grade related to the class’s evaluation?

Some things that could be related to the final class grade: Gender of the student? Age? Sophomore, or Jr. or Sr.? GPA? Expected grade at the beginning of the course? Class section? Gender of instructor? What did you think of the instructor’s personality? Did you think the instructor was fair? Had you heard anything about the class before you took it? Had your heard about how hard the class was? Your overall impression of the class and instructor before the class began? The final evaluation you gave the class and instructor?

The Multiple regression in SPSS looks like this:

All of those variables accounted for 40.2% of all the differences in the students’ final grade. There is less than 1 chance in a 1000 that these variables are not related to the final grade!

When all these variables are put together, as they are in the real world, only the instructors gender, what section a student took, the students’ GPA, and the evaluation the students gave to the instructor were related to the final grade.

Caring = Evaluations But what is “Caring”??

But I know that this is not true!

Forced entry by significance….

Path Diagram

Question: What predicts the evaluation a class and instructor will get?

The final evaluation of the class and instructor is related to (in order): Expected grade in Week 16 Actual grade in Week 16 Final grade for the class Note: If all these grades were the same thing, only one would be related.

If we add variables one at a time, sometimes the answer is different. Notice below how the deserved grade at Week 16 becomes important. Why?

This diagram shows that it is the expected grade at Week 16 that is predicting the evaluation of the Class and instructor.

This diagram shows that it is the expected grade at Week 16 that is predicting the evaluation of the Class and instructor. The other grades are being used by students to estimated the expected grades.