For this discussion, you are to use the following website: https://www.census.gov/acs/www/data/data-tables-and-tools/data-profiles/2017/(Links to an external site.)

• On the landing page, type in the name of your state, and then the name of your city or place.
• Click on "Get Data Profile".
• On the new page, you will see links to 4 sets of information on your area:
  • Social
  • Education
  • Housing
  • Demographic
• Choose any two variables you think might be related and find them by using the links to the related set. In the tables, locate the variables you chose to work with. For example, you could use the number of rooms (in a house) under Housing and household incomes and benefits under Economy.
• Find the values for each of your two variables for several years. For example, you might use the number of rooms and household income for the years 2012- 2017.
• Use Excel to make a scatterplot and to find the correlation coefficient.You should then have 6 points on the scatterplot, one for each year.

Share your scatterplot and correlation coefficient in your post and use them to address the following in your discussion post:

• Why did you think a relationship exists between the two variables you chose?
• Based on the Excel scatterplot and output
  • State what type of relationship exists: Negative, positive, or none.
  • Describe the relationship in words including what happens to one as the other changes. For example, as the number of rooms in a house increases, does the family income increase as well?
• Does the statistical information you obtained support or refute your alternative hypothesis that a relationship exists?
  • How?
  • If you did not find a relationship, why do you think that is?
• What is the value to knowing there is a correlation between the variables? For example, what businesses might flourish in a wealthy area?
• Would another variable better explain the relationship?
• How might the city use such information to make improvements? For example, if you found a relationship between crime and poverty would it make sense to make addressing poverty a priority?
• Can you conclude that one variable is causing the other? Why or why not?