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

Celsius/°C | CO_{2} bubbles/minute |
---|---|

19 | 0.6 |

28 | 2.9 |

29 | 4.3 |

34 | 15.7 |

39 | 21.3 |

- ______________ Determine the slope of the linear regression (best fit line) for the data.
- ______________ Determine the y-intercept of the linear regression for the data.
- ______________ Use the slope and intercept to calculate the predicted bubble rate for 24°C?
- ______________ Use the slope and intercept to calculate the predicted temperature for a bubble rate of 10 bubbles per minute?
- ______________ Does the relationship between temperature and bubble rate appear to be linear, non-linear, or random (no relationship)?
- ______________ Determine the correlation coefficient r.
- ______________ Based on the linear regression, does yeast respiration as measured by the bubble rate increase or decrease with increasing temperature?
- ______________ Is the correlation positive or negative?
- ______________ Is the correlation none, weak, moderate, strong, or perfect?
- ______________ Determine the coefficient of determination.
- ______________ What percent in the variation in temperature accounts for the variation the bubble rate?
- ______________ Can we safely predict the bubble rate for 100°C?
- Why can we or why can we not safely predict the the bubble rate for 100°C?
- 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.

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