Open the related Baseball data set in Power BI. The data set is a collection of batting statistics for 331 baseball players who played in the American League. Because baseball batting averages tend to be highly variable for low numbers of at bats, we should restrict our data set to those players who had at least 100 at bats. This leaves us with 209 players.

What are some of the facts we can intuit from the data ? As a baseball scout, there are certain player characteristics that we may need to round out our player lineup. We can determine which players will best fit our model team from the data provided in the table.

Would we expect to discover a correlation between a players batting average and their slugging percentage ? What about stolen bases and age ? Or Strikeouts and Home Runs ? What does the data look like ?

1. Construct a scatter plot of Home Runs vs Batting Average.

2. Next construct a scatter plot of Home Runs vs Strikeouts.

3.Informally, is there evidence of a relationship between Batting Average, Home Runs, and Strikeouts ? Do players that swing for the fence tend to strike out more ?

4.What would you say about the variability of the number of home runs, for those with higher batting averages?