Suggested Statistical Analyses

The datasets provided here offer opportunities to conduct a wide range of statistical analyses. Consistent with the focus of the book, particular emphasis is placed on descriptive statistics and inferential statistics, including chi-square, t-tests, analysis of variance (ANOVA), correlation, and simple and multiple regression. However, the datasets may also support other statistical techniques beyond those covered in the book.

Readers are encouraged to explore the datasets, develop their own research questions, and determine which statistical techniques are most appropriate based on the variables available, their levels of measurement, and the assumptions associated with each analysis. Not every dataset is suitable for every statistical technique.

Available Files

Select a file below to download a dataset or supplemental file. Dataset names correspond to the names used in the book. The files accompany examples, exercises, and analyses presented in the book. SPSS (.sav) files contain datasets used for analysis, while Excel (.xls or .xlsx) files may be used to create or prepare datasets or provide supplemental data for additional exploration and practice.

2018 National Justice Survey.sav — SPSS Dataset

Description: National survey data examining public attitudes toward police and other institutions, neighborhood safety, police legitimacy and treatment, cooperation with police, crime-control policies, and respondent demographic characteristics.

Applications: Examining public trust and confidence in police and other institutions, perceptions of police legitimacy and treatment, willingness to cooperate with police, attitudes toward crime-control policies, and differences across demographic groups.

FBI UCR 2000 to 2019.xlsx — Excel File

Description: FBI Uniform Crime Reporting data provided in Excel format for use with the book’s data-management exercises.

Purpose: Demonstrates how to import an Excel file into SPSS and prepare the imported data for use in SPSS.

MPD Adverse Action.xlsx — Excel File

Description: Original Washington, D.C. Metropolitan Police Department adverse action data obtained from the DC Open Data portal.

Purpose: Provides the original data used in the Chapter 12 exercise, demonstrating how AI can assist with reviewing, cleaning, and preparing a real-world dataset for statistical analysis.

MPD Adverse Action with New Variables.xlsx — Excel File

Description: Prepared version of the MPD adverse action data containing new grouped variables created during the Chapter 12 data-cleaning and preparation exercise.

Purpose: Demonstrates the transition from the original open-access data to a structured dataset suitable for import into SPSS and subsequent analysis.

MPD Adverse Action Dataset.sav — SPSS Dataset

Description: Analysis-ready SPSS version of the prepared MPD adverse action dataset containing the variables developed during the Chapter 12 exercise.

Applications: Used to demonstrate statistical analysis and verification in SPSS after using AI to assist with data preparation, including crosstabulation and chi-square analysis.

MPD Adverse Action Dataset Cleaned.sav — SPSS Dataset

Description: This is a cleaned and enhanced version of the MPD adverse action dataset containing variable labels and additional variables created to facilitate statistical analysis. Selected discipline classifications were also reviewed and recoded when the disciplinary action clearly belonged in another category.

Applications: Provides an analysis-ready dataset for conducting additional statistical analyses in SPSS. Original variables are retained alongside grouped and recoded variables, allowing users to examine the original data while using the enhanced variables for analysis.

National FF Deaths 2018.sav — SPSS Dataset

Description: Dataset containing information on 87 firefighter fatalities in 2018, including firefighter age, rank, and classification, cause and nature of death, duty and emergency status, activity at the time of death, property type, and state.

Applications: Used to explore firefighter fatality patterns and demonstrate the analysis of both categorical and continuous variables in SPSS.

National FF Deaths 2014 to 2018.sav — SPSS Dataset

Description: Dataset containing information on 457 firefighter fatalities occurring from 2014 through 2018. Variables include firefighter age, rank, and classification, cause and nature of death, duty and emergency status, activity related to the death, property type, state, and geographic region. The dataset also includes recoded and grouped variables created to facilitate statistical analysis in SPSS.

Applications: Used to examine patterns in firefighter fatalities across multiple years and explore relationships among firefighter characteristics, circumstances surrounding fatalities, and causes and nature of death.

Normal and Skewed Simulation.sav — SPSS Dataset

Description: This is a simulated dataset containing 500 simulated cases designed for instructional purposes. The data do not represent real individuals or actual public safety agency records. Variables include income, job satisfaction, overtime hours, and response time, with normal, positively skewed, and negatively skewed versions of each variable. The dataset also includes profession, gender, and experience level.

Applications: Used to demonstrate and compare normal, positively skewed, and negatively skewed distributions and to examine how the shape of a distribution affects descriptive statistics and interpretation.

Simulated Public Safety Personnel Dataset.sav — SPSS Dataset

Description: This is a simulation dataset containing 250 simulated public safety personnel representing dispatchers, firefighters, paramedics, and police officers. The data were developed for instructional purposes and do not represent real individuals or actual public safety agency records. The dataset includes a wide range of demographic, professional, organizational, attitudinal, and performance-related variables.

Applications: Used throughout the book to demonstrate data management, descriptive statistics, and a variety of statistical analyses using public safety–related research questions. Its broad range of variables allows students to explore relationships and differences involving topics such as job satisfaction, organizational support, mental health, risk perception, training, performance, experience, and other characteristics of public safety personnel.

State Crime Data 2022 with Rates.sav — SPSS Dataset

Description: State-level crime dataset containing 2022 crime data for all 50 states. Variables include state population, geographic region, number of participating agencies, counts for numerous crime categories, and corresponding crime rates per 100,000 population.

Applications: Useful for comparing crime patterns across states and geographic regions and for examining relationships among different types of crime. The inclusion of both crime counts and population-based rates allows students to explore why rates are generally more appropriate than raw counts when comparing jurisdictions of substantially different population sizes.

State Data for Correlation and Regression.sav — SPSS Dataset

Description: State-level dataset containing data for the 50 states and Washington, D.C., with variables covering crime, demographics, socioeconomic conditions, corrections, justice expenditures, education, unemployment, homelessness, and other social indicators.

Applications: Used in the book to demonstrate correlation and regression analyses and to explore relationships among crime, demographic, socioeconomic, and other state-level characteristics.

State Dataset 2021–2022.sav — SPSS Dataset

Description: State-level dataset containing data for the 50 states and Washington, D.C. Variables include crime and arrest rates, corrections and incarceration, justice expenditures, demographic characteristics, unemployment, poverty, education, homelessness, substance use, gun-related deaths, and other social and economic indicators.

Applications: Provides a comprehensive dataset for exploring relationships among public safety, criminal justice, demographic, social, and economic characteristics across states. Suitable for descriptive statistics, group comparisons, correlation, and regression analyses.

Vancouver Crime Data 2014 to 2023.sav — SPSS Dataset

Description: Annual crime data for Vancouver, Washington, covering 2014 through 2023. Variables include population and annual counts and rates for violent crime, property crime, murder, rape, robbery, aggravated assault, burglary, larceny/theft, motor vehicle theft, arson, and total crime.

Applications: Used to examine changes in crime over time and to demonstrate trend analysis and simple linear regression. The dataset allows students to explore how crime counts and rates change across years and to use regression to estimate and forecast crime trends.

Fire Response Demonstration Dataset.sav — SPSS Dataset

Supplemental Dataset — Not Used in the Book

Description: This is a simulated dataset containing 480 simulated fire service incidents designed for instructional purposes. The data do not represent actual incidents or fire departments. Variables include department, geographic region, fire station, response time, weather, snowfall, travel distance, call priority, staffing, and traffic conditions.

Applications: Provides a flexible supplemental dataset for practicing many of the statistical analyses demonstrated in the book, including descriptive statistics, chi-square, t-tests, ANOVA, correlation, and simple and multiple regression. The dataset allows users to develop and test a variety of public safety research questions using the same dataset.