Geography 370 Assignment 6

Part I. 
For this assignment, data was given about crime rates and lunch prices to see if there was a relationship between the two. Some people believed that as free lunches increase, the crime does as well. To explore the causation of the potential relationship, a regression analysis was run.

Looking at these variables, we can detect a regression equation: 

Y= 21.819 + 1.685X

Even though there is a positive slope in the trend of this data, it is a weak one between the two. The R squared result of this is a significant way of telling the strength of this relationship. It is only .173, meaning that the crime rate of the town only is only influencing lunch distribution by about 17%. Since the significance value is at .05, we would fail to reject the hypothesis, saying that there is not a significant relationship between the two.

Part II.

This portion of the assignment covered data that had been taken from 911 calls over a period of time. The data that was given contains information about the people's calls, such as where they were calling from and their background history. A regression was run through SPSS to determine if there are relationships of causation between the different variables chosen. The variables with the most notable relationships with crime calls are: low education (.562 r squared), renters (.616 r squared), and low education efficiency (.551 r squared value).