Years estimated vs. years actual
  1. It is appropriate to use the year event occured as the explanatory variable because the estimation depends on the actual year
  2. the scatterplot would have the same x and y coordinates if guessed correctly
Union percent vs. membership
Union percent vs. membership
  1. I used union membership percent as the explanatory becuase the more members there were the more stikes were held
  2. There is a positive association between number of strikes and membership percent
  3. the second scatterplot shows the plot using the number of strikes as the explanatory variable
  4. there is a positive association with the second plot
  1. The bar graph helps determine the huge difference between the average personal income and the governors salary per state
  2. Yes there is a positive association between the variable as the higher the personal income the larger the governors salary
  1. after seeing all the data no there is no association the points seem to be scattered everywhere
  2. there is one data point where the personal income is $55k which is the highest, yet has an average governors salary. This makes it stand out because most states with high personal income also have a high governors salary

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