Describing and Displaying Bivariate Data Practice Questions

To review these concepts, go to Describing and Displaying Bivariate Data Study Guide.

Describing and Displaying Bivariate Data Practice Questions

Practice

A researcher thought that the average high temperature in March for U.S. cities could be explained by latitude. He collected data on the average high in March and the latitudes for 16 U.S. cities. The data are listed in Table 8.2.

1. We have two variables: temperature and latitude. Specify which variable is the explanatory variable and which is the response variable.
2. Create a scatter plot of the data and describe the relationship between latitude and average temperature in March.

Look again at the data on the relationship of the average monthly temperature in March and latitude.

3. Find the z-scores associated with the average monthly temperature in March and the latitude.
4. Find the Pearson's correlation coefficient for these data.
5. Relate the correlation coefficient r to the graph.

Solutions

1. Explanatory variable = latitude; response variable = temperature.

2.  

   

   As the latitude increases, the average temperature decreases.

3.  

   

4. Pearson's correlation coefficient r = – 0.92
5. r = – 0.92 suggests a strong negative relationship between X and Y, latitude and temperature.