Discussion Questions: 1. Given a list of variables collected from Contra Costa College students: . GPA (grade point average) . Average weekly hours spent working at a job o Average weekly hours spent watching television . Average weekly hours spent doing homework o Average hours of sleep a night o Hourly wage o Height o Weight o Age . Gender . Race A. Choose two variables that you think will be positively associated. Explain your reasoning. B. Choose two variables you think will be negatively associated (You may reuse variables). Explain your reasoning. C. Choose two variables you think will not show association in a scatterplot (You may reuse variables). Explain your reasoning. 2. This scatterplot shows the relationship between neck measurement (cm) and weight (Ib) for 252 men. The linear correlation coefficient r is 0.83. 400 300 Weight (1b) 200 100 30 32 34 36 38 40 42 44 46 48 50 52 Neck (cm) A. If we change the weights from pounds into kilograms, what is the effect on the correlation? B. If a man is removed from the data set, the correlation decreases only slightly from 0.83 to 0.81. Why do you think the change in the correlation is so small? 3. For the 130 adults in this sample, heart rate is measured in beats per minute and body temperature is measured in degrees Fahrenheit. StatCrunch gives the following linear regression results: Dependent Variable: Temperature Independent Variable: HeartRate Temperature = 0.026334549 (HeartRate) + 96.306754 Sample size: 130 R (correlation coefficient) = 0.2536564 Interpret the slope and the y-intercept for the regression line using the context for the data if possible