Lab9 - Lab #9 Simple Linear Regression SOLUTION Due...

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Lab #9 – Simple Linear Regression SOLUTION Due Wednesday, April 16, 2008 at the beginning of class For this lab we will the Children data set used in the previous lab. This data set is on the worksheet titled “Children” in the accompanying Excel file used in Lab #8. The data set is from Lewis and Taylor, 1967 (and taken from the SAS documentation.) The variables are: Sex (f for female, m for male) Age (in months) Height (in inches) Weight (in pounds) 1. Using SAS, find the least squares regression line to predict a child’s height from the child’s age. Give the equation for the regression line below. ( ) ˆ 38.51927 0.13894 h age =+ 2. Using SAS, find the least squares regression line to predict a child’s age from the child’s height. Given the equation for the regression line below. () ˆ 21.52159 3.03028 a height =− + 3. Based on your answers above, how much (on average) does a child grow in a month? in a year? in a month: 0.13894 inches in a year: 12 × 0.13894 = 1.66728 inches 4. What percent of the total variation seen in heights can be explained by the differences in the children’s ages? 42.10% 5. Predict height from age. Fill in the table below: Age Predicted Height in years in months in inches 12 144 58.52663 13 156 60.19391 14 168 61.86119 15 180 63.52847 16 192 65.19575 17 204 66.86303 18 216 68.53031 19 228 70.19759 20 240 71.86487
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6. Predict age from height. Fill in the table below: Height Predicted Age in inches in months in years 52 136.053 11.33775 54 142.1135 11.84279 56 148.1741 12.34784 58 154.2347 12.85289 60 160.2952 13.35793 62 166.3558 13.86298 64 172.4163 14.36803 66 178.4769 14.87307 68 184.5375 15.37812 70 190.598 15.88317 7. Bob is 18 years old.
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Lab9 - Lab #9 Simple Linear Regression SOLUTION Due...

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