MS 150 Statistics Quiz 04 • Name:

19 September 2008

Data table from SC 120 Biology yeast respiration rate experiment. Treat the data as being linear.

1. ______________ Determine the slope of the linear regression (best fit line) for the data.
2. ______________ Determine the y-intercept of the linear regression for the data.
3. ______________ Use the slope and intercept to calculate the predicted bubble rate for 24°C?
4. ______________ Use the slope and intercept to calculate the predicted temperature for a bubble rate of 10 bubbles per minute?
5. ______________ Does the relationship between temperature and bubble rate appear to be linear, non-linear, or random (no relationship)?
6. ______________ Determine the correlation coefficient r.
7. ______________ Based on the linear regression, does yeast respiration as measured by the bubble rate increase or decrease with increasing temperature?
8. ______________ Is the correlation positive or negative?
9. ______________ Is the correlation none, weak, moderate, strong, or perfect?
10. ______________ Determine the coefficient of determination.
11. ______________ What percent in the variation in temperature accounts for the variation the bubble rate?
12. ______________ Can we safely predict the bubble rate for 100°C?
13. Why can we or why can we not safely predict the the bubble rate for 100°C?
14. What would you tell an SC 120 Biology student who asked whether the temperature is a good predictor of the respiration rate for the yeast?

The following table and data are under consideration in the three questions below.

15. ____________________ What is the nature of the relationship: linear, non-linear, or random?
16. ____________________ Would performing a linear regression and correlation on this data be statistically valid?
17. ____________________ Why or why not?