A chart showing a scatter plot of estimated years and actual years of events.

A scatter plot chart of predicted years and actual years of events that occured in the 1900s

  1. Since year event occured is the actual year, this is the indapendant variable, it cannot be moved, while, the "estimated year occurred" is the dependant variable, it can be moved.
  2. The points would only move alongside the Y-axis.

Showing how certain amounts of strikes and union percentages can be placed into a graph

  1. The explanatory variable is Strikes and lockouts, while the response is Union Membership percentage. This is due to that fact that Union Membership is the dependant variable, being changed by the amount of lockouts.
  2. A positive relationship, as the amount of lockouts increase so does Union Membership.
Another chart showing the same data with the x-axis and y-axis switched on how strikes and percentages can be placed on a graph.
  1. This list shows the same data, but, the x-axis and y-axis data have been flipped.
  2. There is again a positive relationship, and yes, the data is related.
A chart showing the personal incomes and Governor salaries of some states.
A grap showing the personal incomes and governor salaries in a bar chart of some states.
  1. The bar graph helps show exactly how much more the Governor's income is and the states.
  2. There is an association in the variables, but it is not very clear in the scatter plot.
A graph showing the salaries of governors and personal incomes of the public in all 50 states.
  1. There is a positive relation, as the personal capita increases, so does the governor's salary.
  2. Yes, the lowest point on the graph, and the point furthest to the right. There are other states who earn this amount of personal income, so why is the governor's income so low? Same goes for the point on the right, why is the governor's income so low, but the personal income so high in comparison to respective points to the left and of it?