projectF - Time = 8.84 0.940(7 Time = 8.84 6.58 Time =...

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Project F Michael Kundrat April 11, 2008 Math 160H Kuby
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2) The population is all MCC students. Independent variable is the distance to school and the dependent variable is the time it takes to get to school. 3) Data Display Row Distance Time 1 12 17 2 7 15 3 16 20 4 7 15 5 8 15 6 8 22 7 10 18 8 25 30 9 13 40 10 7 12 11 15 15 12 25 45 13 10 30 14 12 12 15 1 2 16 30 27 4) 30 25 20 15 10 5 0 50 40 30 20 10 0 Distance Time 27 2 12 30 45 15 12 40 30 18 22 15 15 20 17 Distance vs. Time 5) Correlations: Distance, Time Pearson correlation of Distance and Time = 0.664 P-Value = 0.005 There is a weak positive correlation, Ho: There is no correlation Ha: There is correlation
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Reject Ho. Mean of the independent variable: 12.88 Mean of the dependent variable: 20.94 6) 30 25 20 15 10 5 0 50 40 30 20 10 0 Distance Time Distance vs. Time Regression Analysis: Time versus Distance The regression equation is Time = 8.84 + 0.940 Distance 7) My independent variable (distance) is 7 miles from school.
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Unformatted text preview: Time = 8.84 + 0.940(7) Time = 8.84 + 6.58 Time = 15.42 Average time for students living 7 miles from school is 15.42 minutes to get to school. 8) The y intercept is 8.84 and the slope of the line is 0.940 / 1. The slope equals the change in y over the change in x, or the change in time / the change in distance. There are a couple of outliers that lie far from the best fit line. The population is all MCC students but the sample size is the MTH 160H class of 16 students. Although the data has a positive correlation it is very weak because it is 0.664, it would be much stronger if some of the outliers were absent. The line of best fit could be very useful if a MCC student wanted to calculate an average time to leave their house in the morning to get to school on time....
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projectF - Time = 8.84 0.940(7 Time = 8.84 6.58 Time =...

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