The "year event occured" column is used appropriately used as the explanatory variable becasue the response variable, estimated year, is the result of an estimation of when a person thinks the event actually occured.
If I guessed each year correct the scatter plots would be identical.
I used "Union Memebership Percentage" as my explanatory variable because you can see from it that as membership grows so does the number of strikes and lockouts.
The relationship between the union membership and strikes/lockouts is directly proportional.
My second sctter plot depicts the decline in union mebership from the years 1940-2010.
The two variables have a negative correlation. As time increases (decades), the "Union Membership Percentage" decreases.
The bar graph helps clearly depict the difference in salaries between the states Governor and the states citizen average salary.
There doesn't looks to be any association between the two variables in the scatter plot. As the Governor's salaries rise most of the state average salaries seem to stay around the $50,000 mark.
From this larger set of data we can more clearly see that the average salary for most states lingers around $40,000. The governors salaray for each individual state is quite drastically different.
One data point that sticks out to is that of Maines. The Maine Governor is the governor with the closest salary to its state average (70,000 compared to 37,300). Other than this most governors make much more that the states average income.