HFIT-565
Assessment & Evaluation of Health Fitness Parameters
Fall Semester 2009
Dr. Marc Schaeffer
There are three examples on this page. You should study them and I strongly suggest replicating the first two. Remember for our work, we need to express our r, Multiple R, and p to three decimal places.
The output from the first Excel solution corresponds to the problem in the Lecture #6 notes involving the prediction of a Final Exam score from a previous regular Exam score. You should probably enter the 7 ordered pairs and try to replicate the following frames representing each of the following three frames for the Summary Output & Line Fit Plot, Anova Source Table with Coefficient Summary, and the Residual Output. I have shaded key elements in each of these frames. Please remember that there are three solutions on this page, two of which are related to Lecture #6 notes.
First - here are the raw data for X(Exam scores) and Y (Final Exam scores)
Next, we have the Summary Output and the Plot
Next is the Anova Source Table and Coefficient Summary, followed by the Residual Output
back to Lecture 6 page data display
The output from the next Excel solution corresponds to the problem in notes dealing with the prediction of a Mid-term Exam score from a previous Quiz score. These are real data for the class in the Fall semester 1999. The Mid-term Exam scores are rounded to whole numbers in the section you were just reading in the Lecture notes, however the scores below reveal the Mid-term Exam scores to the nearest tenth. If you try to replicate this solution you should use the decimal scores rather than the whole numbers. Each of the component presented above are included below.
First - here are the raw data for X(Quiz scores) and Y (Mid-term Exam scores)
Next, we have the Summary Output and the Plot
Next is the Anova Source Table and Coefficient Summary, followed by the Residual Output
Note the yellow box above is showing predicted Y values for each of three different X values. The predicted Ys were derived by substituting each of the X values (70, 80, 90) one at a time into the equation for the best fitting regression line (line of best fit): Y 42.668 + 0.596X.
back to Mid-term & Quiz score problem in Lecture 6
Chapter 8, page 166 Burger King (fat related to protein) example contains the following data. Please read the material in the text discussing this problem from page 166 - 170, and also the computer printout on page 183.
