Plot of estimated event dates occured versus actual event dates occured
    Question 1:Why is it appropriate to use the variable “year event occurred” as the explanatory variable and “estimated year event occurred” as the response variable?
    Answer: The "year event occurred" is the independent data and cannot be changed while the "estimated year event occurred" can be different depending on different people.
    Question 2: What would the scatterplot look like if you had guessed the correct year for each event?
    Answer: The plot would look like a straight line and its eqution would be y = x.
Union data using lockouts as explanatory variable
Union data using member percentage as explanatory variable
    Question 1:Which variable did you use as the explanatory variable when relating the number of strikes and lockouts with the percentage of the total labor force with union membership (in your first scatter plot)? Why?
    Answer: I used "strikes and lockouts" as explanatory variable since the data is independent.
    Question 2:What type of association is there between the number of strikes and lockouts with the percentage of the total labor force with union membership?
    Answer: Positive association.
    Question 3: Explain what your second scatterplot shows.
    The second plot shows the higher strikes and lockouts, the larger percentage of labors with union membership.
    Question 4: What type of association is there between the variables you related in your second scatter plot, or are the variables not associated?
    Answer: Positive association.
Governor data in clustered column
Governor data in scatterplot
    Question 1:Which aspects of the data does the bar graph help interpret?
    Answer: The bar graph interprets the large difference between the governor's salary and the personal income.
    Question 2:Is there an association between the variables in your scatterplot? Explain
    Answer: There is no specific association between the variables since the personcal income doesn't constantly go up or go down as governor's salary goes up.
Large Governor data in scatterplot
    Question 1:Now that we can see all the states, are there any trends or associations in the data? Explain
    Answer: The higher governor's salary tends to have higher personal income. Therefore, there is a positive trend.
    Question 2:Are there any data points that appear to stand away from the rest of the data? If so, which one(s) and what makes them stand out.
    Answer: I don't think there is any data point stand out.

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