Analyzing Criminal Justice Data Report

Testing Differences and AssociationProject #2

The purpose of this project is to help you get further accustomed to working with data and being able to test for differences. In this assignment, you will be working with crime data for an individual state. Each student will be assigned a different state to complete this assignment.This project builds off of the first project, so you are assigned the same state as before. For example, if you were assigned Massachusetts for the first project, you are assigned Massachusetts again for this project.In addition to working with the data in Excel, you will be writing a short report analyzing your results in Microsoft Word. In the steps below it is noted when tables/figures created in Excel should be copied and pasted into your report in Word.Results that are reported in your written report should also appear in your final Excel file. Please feel free to use separate tabs in your Excel file to keep things organized. Your data file for this assignment shouldonly include what you do for this project.This assignment is graded on 100 possible points and is worth 20% of your final grade.Obtaining and Preparing Crime Data for AnalysisYou will be using the same FBR UCR data as your first project. You should still have this data saved from the previous project if you need to re-download it, follow these instructions: Connect to the FBI’s UCR website and navigate to the “Crime in the U.S.” page for the year 2015(https://ucr.fbi.gov/crime-in-the-u.s/2015/crime-in-the-u.s.-2015). Open Table 8(Offenses Known to Law Enforcement by State by City, 2015). Select your assigned state then download the crime data for your state and save thefile to your computer.Hide all variables except for City, Population, and Robbery. Comparing Robbery Ratesin Big versus Small Cities1)In your crime data file, you should already have calculated the robbery rate per 100,000 residents for each city in your sample. If you do not have this, do so.2)In a new column, create a new variable that classifies cities into two groups: 1) Small (less than 10,000 residents) and 2) Large (10,000+ residents). (Note: It may be helpful to “sort” data based on populationfirst).a.In your report, state the null hypothesis and two-tailed research hypothesis for examining this relationship.Also, identify the independent and dependent variables in this analysis.3)Using the “Data Analysis Tool”, conduct atwo-tailedt-test with unequal variances assumed that tests for the difference in mean robbery rates betweenlarger and smaller citieswith an alpha= .05. a.Create a table in your report that includes for both groups the mean, variance, and number of observations as well as the degreesof freedom, t statistic (t obtained value), critical t value and p-value for two-tailed tests (Note: if your p-value is extremely small, you can report it in your table as <.001).b.Describe and interpret the means for the two different groupings of cities,including the mean difference between the two groups (you will need to calculate this on your own, it

is not included in the t-test output). Describe and interpret the results of your t-test, and make a conclusion about whether or not to reject the null hypothesis.Analyzing Police Presenceand Robbery RatesIn this section, we are going to explore the relationship between robbery rates and law enforcement officers per capita. Specifically, we are interested in learning whether law enforcement officers are associated with robbery rates. First, we want to download data on law enforcement officers. To do so, return to the FBI UCR website for 2015 and download the police employee data for your assigned state. Go to Table 78 (Full-time Law Enforcement Employees, by State by City, 2015) and download data for your state (https://ucr.fbi.gov/crime-in-the-u.s/2015/crime-in-the-u.s.-2015/tables/table-78/table_78_full_time_law_enforcement_employees_by_state_by_cities_2015.xls/view). Copy and paste the law enforcement data into a new spreadsheet/tabin your robbery data file.1)Deletethe columns for “Total law enforcement employees” and “Total civilians.” Calculate the rate of “Total officers” per 1,000 residents in each city in your sample.2)Match officers per 1,000 residents to your robbery rate spreadsheet by city. (Note: Using the “VLOOKUP” function will make this easier). If there are cities in your sample that do not report the number of officers, then filter those cases out (Filter -> uncheck “NA” which is what it will appear as if you use “VLOOKUP”). Copy and paste this filtered data into a new tab.a.In your report, state the null hypothesis and two-tailed research hypothesis for examining this relationship.Also, identify the independent and dependent variables in this analysis.3)Create a scatterplot showing the relationship between robbery rate per 100,000 and police officers per 1,000 residents.In the scatterplot, theindependent variable should be along the x-axis and thedependent variable along the y-axis.a.Copy this figure into your report and interpret what you see.4)Calculate and test the significance of the correlation(alpha = .05)between robbery rate per 100,000 and police officers per 1,000 residents.(Note: In order to get statistical significance, you want to use the “Regression” option in the “Data Analysis Tool”).a.Reportand interpretyour results.5)Calculate and test the significance of the correlation (alpha = .05) between robbery rate per 100,000 and police officers per 1,000 residents for only the 10 largest cities.(Note: In order to get statistical significance, you want to use the “Regression” option in the “Data Analysis Tool”).a.Report and describe your results, and note any chance in the results when narrowing the analysis to just the 10 largest cities.Submission MaterialsEach student will be submitting two files for this assignment: 1) a written report in Microsoft Word; and, 2) acopy of your finalized dataset in Excel.Under the “Assignment” section of the course Canvas page, there is a corresponding folder where you can submit this assignment. Please be sure that both files are uploaded before submitting in Canvas.Due Date:12/9/20 (Wednesday) by 11:59 p.m.