Chart description
  1. a.) It is appropriate to use the variable "year event occurred" as the explanatory variable because it is a fact and cannot be affected by any other variable. The variable "estimated year event occured" is the response variable because it can be changed by other variables such as my intellegance or my state of mind during the time I guessed the year of the events. This response variable is a dependant variable while the explanatory variable is an independant variable.
  2. b.) If I had guessed correctly on every event, then the scatterplot would match up the numbers on the y-axis and the x-axis for each event and would show a 45 degree diagnal line going from the lower left corner to the upper right corner of the graph.
first chart
second chart
  1. a.) I chose the number of lockouts/strikes as my explanatory variable because both variables were subject to change but i wanted to see if the number of stikes/lockouts affected the how much of the workforce would participate.
  2. b.) There is a positive association between the two variables. As the number of strikes.lockouts increase, the percentage of the work force that attends also increases so they are directly proportional.
  3. c.) My second scatterplot shows the number of strikes/lockouts over 1000 people that occurred from 1950 to 2010
  4. d.) The second scatterplot shows a negative association betweenthe two variables. As the years increase, the number of strikes decrease so they are indirectly proportional.
third chart
fourth chart
  1. a.) The bar graph helps visualize the pay gap between the governor's salary and what the avergae person makes in that given state. Its harder to interpret that gap when just given numbers so the bar graph helps show the difference.
  2. b.) There is no association between the variable on the scatterplot. No set trend can be seen from the data.
fifth chart
  1. a.) Even though there are all fifty states, there still doesn't seem to be an apparent trend or association.
  2. b.) The only real outlyer is Connecticut which has the highest average income per capita and that puts its data point further to the right than the other ones enough that it is noticable.

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