Wine intake x 2.5 8.5 15.5 26.5 (grams per day) Relative risk y 1.00 1.08 1.15 1.22 (a) Make a scatterplot of these data. Based on the scatter- plot, do you expect the correlation to be positive or negative? Near ±1 or not? (b) Find the correlation r between wine intake and relative risk. Do the data show that women who consume more wine tend to have higher relative risks of breast cancer? 00

Select the most appropriate response. If the correlation between a person’s age and annual income is 0.60, then the coefficient of determination tells us that: 36% of the variation in a person’s annual income can be explained by the predictor variable age. 36% of a person’s annual income can be explained by their age 60% of the variation in a person’s annual income can be explained by the predictor variable age 60% of a person’s annual income can be explained by their age

Which data has. A stronger linear correlation? Data 1 with an r= 0.7 or data 2 with an r= -0.8? Why?

Describe the error:  Given: The linear correlation coefficient between scores on a math test and scores on a test of athletic ability is negative and close to zero. Conclusion: People who score high on the math test tend to score lower on the test of athletic ability.

Compute the correlation coefficient between the height and weight of the quarterbacks. Round the answer to at least three decimal places.

find t reject or fail to reject

Below is a subset of the data on quality of marriage and quality of parent-child relationship. Using the data provided below, calculate the correlation between the two variables. You should calculate the correlation "by hand" and show your work that led to the solution (take a picture of your hand-written notes and insert it into this document) Quality of marriage Quality of parent-child relationship 1 5 2

Given the scatter plot below, which of the following describes the strength and direction of the data? 10 Weak negative correlation Strong negative correlation Strong positive correlation Weak positive correlation

There is a negative correlation between the average litres of wine consumed by residents of a country and the incidence of national coronary deaths. Explain why correlation in this case does not imply causation by suggesting a third variable z that explains the correlation. Is z a common response or a confounding variable? Draw a digraph illustrating the between x, y, and z