Assignment 3 You have been asked to conduct research on the relationship between neighborhood characteristics and crime. For this assignment you will do the following: Preliminary Work–Examine the...

Assignment 3

You have been asked to conduct research on the relationship between neighborhood characteristics and crime. For this assignment you will do the following:

Preliminary Work–Examine the Code Book

1. 
   

   Develop a hypothesis that examines the relationship between neighborhood characteristics and crime. Your hypothesismustbe approved by the instructor. You will submit your hypothesis for approval as part of your Lab 10 assignment. The format for your hypothesis should beas follows: “As the independent variable (IV) increases, the dependent variable (DV) will increase/decrease (pick 1), while controlling for thecontrol variable (CV).”Select the IV, DV, and CV based on what seems plausible to you.

   
   


2. 
   

   YoucannotusethesamethreevariablesfromtheexamplePowerPoint, the lab, or any of the lectures.You can select NO MORE THAN ONE (1) of the variables used in the examples to formulate your hypothesis.

   
   

a. For instance, if the example hypothesis is asthe percentage of owner-occupied housing in a neighborhood increases, the property crime rate per 1,000 will decrease, while controlling for the percentage of residents living in poverty, you could not select the property crime rate (rate of theft, burglary, and larceny incidents per 1,000) and the percentage of residents living in poverty as the DV and IV, respectively, for your hypothesis.

3. Thereareonlyfour(4)variablesinthedatasetwhichmeasure crime. SelectVIOLRATE(rate of homicide, rape, assault, and robbery incidents per 1,000),RATEVA(violent crime arrest rate per 1,000),PROPRATE(rate of theft, burglary, and larceny incidents per 1,000),ORRATEPA(property crime arrest rate per 1,000) as your measure of crime (the DV). Pick whichever one makes the most sense to you.

a. Make sure you are paying attention to the variable you select. For example, there is a difference between the violent crime rate (VIOLRATE), which is the rate of murder, rape, assault, and robbery incidents per 1,000, and the violent crime arrest rate per 1,000 (RATEVA).

4. Fromtheothervariablesinthedataset,youwillselectoneIVforyour hypothesis and one CV (a rival causal factor that also may explain crime–i.e., your DV).

Analysis–Lab 10 will demonstrate Correlation and OLS Regression and their related features

1

1. 
   

   Prepare basic descriptive statistics of the variables in your analysis: the number of cases, the minimum/maximum values, the mean, and the standard deviation–you will learn how to do this in Lab 11.

   
   


2. 
   

   You will evaluate how your hypothesis meets the three criteria for causal inference:

   
   

   a. Correlation is a systematic relationship between the IV and DV.

   
   

i. To do this, you use the correlation matrix to examine the

relationship between your two IVs and the DV. b. Time order establishes the IV precedes the DV in time.

i. To determine this, look in the code book to see when the data were collected. If they were collected in the same year, then causal ordering is a problem and limits what you can conclude from the analysis.

c. No spuriousness means the relationship between the IV and DV is not due to some other outside factor.

i. To do this, you add your control variable to your analysis using multiple regression. So, in this analysis you will have 1 IV, 1 CV, and 1 DV.

Report–Lab 11 will demonstrate how to create a PowerPoint presentation

1. 
   

   ThePowerPointpresentationofyourworkwillinclude:

   
   
   
   
   1. 
      

      Title Page

      
      
   
   
   2. 
      

      Hypothesis

      
      
   
   
   3. 
      

      Operationalization of the concepts

      
      
   
   
   4. 
      

      Descriptive statistics (Table 1; explained in Lab 11)

      
      
   
   
   5. 
      

      Evaluation of causal inference:

      
      
      
      
      1. 
         

         Correlation matrix between the IVs and DV (Table 2)

         
         
      
      
      2. 
         

         Timeorder(obtainedfromcodebook)

         
         
      
      
      3. 
         

         NoSpuriousness:norivalexplanationdrivingthe

         
         

         results. You will do a multiple regression analysis to

         
         

         determine this (Tables 3a/3b and 4a/4b)

         
         
      
      
      
      
   
   
   6. 
      

      All six tables must be in academic format (see Lab 9).

      
      
   
   
   7. 
      

      Conclusion (was your hypothesis supported based on the

      
      

      three criteria for causal inference?)

      
      
   
   
   
   


2. 
   

   For Assignment 3 you will be required to provide a brief write-up of your

   
   

   analysis and the results. You will need to write a 4-6-page, double-spaced paper that, essentially, discusses each slide of your PowerPoint presentation. The example presentation I will provide, will reference the details you should be focusing on when discussing your tables. However, your PowerPoint presentation should only serve as a reference in terms of how your paper is set up (i.e., you should discuss the material in order starting with the first slide).

   
   

   Remember this is a paper, not a summary of your PowerPoint. Therefore, it is paramount your paper flows and makes sense. It should not have

   
   

2

bullets with a couple of sentences. This meansthere should be no reference to any of your PowerPoint slides within your write-up. Think of it as a separate paper, which also means you should not assume your reader will have access to your PowerPoint presentation. Therefore, you need to make sure youinclude your tables from your PowerPoint in your write-up. If you do not include your tables in the write-up and/or refer to the PowerPoint presentation, you will lose points on the assignment. This paper should read just like your first two assignments (i.e., introduction, body of your paper, conclusion, etc.).

Again, you should imagine your reader has no background knowledge of these statistical measures, so you want to make sure you explain everything (e.g., what each element used to demonstrate causality means and whether your variables fulfill them, what the results of each table mean and why you ran these tests, etc.).