Actual Event Date vs. Estimated Event Date
  1. a.) Using "year event occured" as the explanatory variable makes sense because it is set in stone data that cannot change while the "estimated year event occured" data is the response variable because this data depends on what we think the actual year the event occured.
  2. b.) The scatterplot would look like a diagonial line with a positve relationship.
    Number of Strikes vs. Union Membership
    Number of Strikes vs. Union Membership
    1. a.) I used union membership as the explanatory variable because the number of strikes depends on how much union membership there is.
    2. b.) There is a positive relationship with the number of strikes and lockouts with union membership.
    3. c.) The second scatterplot shows how the number of strikes affects the membership percentage.
    4. d.) There is no association.
    Personal Income vs. Governor's Salary per State
    Personal Income vs. Governor's Salary per State
    1. a.)The bar graph helps to interpret the great difference between the governor's salry and per capita income in each state.
    2. b.) There is no association in the scatter plot graph because the points of data are randomly placed and salaries in each state differ with no relation.
    Per Capita Personal Income vs. Governor's Salary
    1. a.)Looking at all the data there does seem to be a positive relationship between per capita income and the governor's salary. As personal income increases so does the governor's salary.
    2. b.) There are a few outliers in the data that dont follow the pattern which makes them stand out.
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