Two variables (Crime rate and CPTED audit rating)- which test to use?


I am a college student currently finishing up my Master’s degree in Applied Geography. I am working on a research project/thesis. The project is focused on Crime Prevention Through Environmental Design, AKA CPTED. CPTED is a theory that certain characteristics of the built environment, such as level of maintenance, level of visibility, and personal touches, can help prevent crime.

To put it simply, I want to see if areas (neighborhood blocks) with more CPTED characteristics also have a lower crime count. My hypothesis is that the areas with a higher CPTED rating will have a lower crime count, and areas with a lower CPTED rating will have a higher crime count.

For my research, I made observations of houses of 6 neighborhoods through a walking audit, and rated all of the houses based on CPTED characteristics. The rating system is 0 (worst) to 4 (best). Higher CPTED ratings are meant to be “better,” meaning these houses have a lower risk of being targeted for property crime.

Once all of the houses in each of the 6 neighborhoods were rated and recorded in a spreadsheet, I assigned each house to a neighborhood block, and the blocks were given the combined average CPTED score.

I then obtained data of crime incidents from the local police department and assigned the crime incidents to the blocks, because most crime reports nowadays only have block-level accuracy, instead of giving specific addresses.

To recap, I have:

A spreadsheet which has a column for average CPTED rating, and a column for Crime Count (per 1,000 houses to normalize the data). You can see this in the below image.

I already ran a regression analysis on this data, and the result shows that as the CPTED rating increases, the crime count decreases. However, this is a somewhat weak inverse relationship, with an R-Squared value of .18. But I now am questioning whether or not a regression analysis is appropriate for this type of study.

My question is:

Could I perform some sort of non-parametric statistic test? I have to admit, that I am still a bit of a novice when it comes to these types of statistics. Are there any non-parametric statistic tests that I could use on this data to determine the relationship between CPTED rating and crime count? I have been encouraged to use a non-parametric test but I am not sure which one, if any, would be appropriate.

Any help or advice is appreciated. Thanks.



Well-Known Member
Hi J,

The fact that there is a correlation between x and y doesn't say that x is the cause for y. It might be that c cause both x and y. and there is a good correlation between x and c.

Low R doesn't say the result is not significant, for this you need to look on the F test p-value for the regression, or T for the specific Coefficient.
It may be high R with an insignificant result or low R with a significant result.

The chart doesn't look like a linear regression ... and I guess the residuals don't distribute normally.

Did you try adding other predictors? like: average salary in the neighborhood, distance from other "bad neighborhoods", level of education ...