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Analyzing the relationship between movie gross and actor salary using scatterplots. This study examines whether stars with high movie grosses have the highest salaries.
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Example 2.7Relationship Between Salaries and Domestic Gross for Movie Stars Analyzing Relationships with Scatterplots
Objective To use StatPro’s scatterplot procedure to illustrate the relationship between movie gross and actor salary.
ACTORS.XLS • Recall that this data set contains information on 66 movie stars including their, Gender, Domestic Gross, Foreign Gross and Salary. • The data may lead us to suppose that stars whose movies gross large amounts have the largest salaries. Is this true?
Scatterplots • We are often interested in the relationship between two variables. • A useful way to picture this relationship is to plot a point for each observation, where the coordinates of the point represent the values of the two variables. • The resulting graph is a scatterplot.
Scatterplots -- continued • After constructing a scatterplot, we can examine the scatter of points. • We can usually see whether there is any relationship between the two variables, and, if so, what type of relationship it is. • We will use a scatterplot to determine if the statement about the relationship between movie gross and salaries is true.
Creating a Scatterplot • To analyze this we need to plot each star’s salary on the vertical axis and the corresponding domestic gross on the horizontal axis. • To create this scatterplot: • Place the cursor anywhere in the data set. • Select the StatPro/Charts/Scatterplot menu item. • Select Salary as the Y variable, Domestic Gross as the X variable and give the chart sheet a name such as Scatter.
Analyzing the Scatterplot • The message is clear. The points tend to move up and to the right. This means that stars in films with large domestic grosses tend to make the largest salaries. • The correlation of 0.61 shown in the chart supports this conclusion. As we will see in Chapter 3, this implies a reasonably strong positive linear relationship between the two variables.