POSC Research 1

Results

Results

Topic 2: Income Inequality and Violent Crime Rates Across U.S. States A. Topic Description The second issue that I might discuss is the connection between the rates of violent crimes and income inequality in U.S. states. The rate of crime is a very diverse phenomenon that can be quite debated by policymakers who tend to discuss the reasons for diversity (Ulmer et al., 2012). Others have argued that crime is reduced by stronger enforcement of laws or increased police expenditure, whereas others have argued that stronger socioeconomic drivers like poverty and inequality play a stronger role. Income inequality is the way in which income is distributed unevenly within a state, which is commonly gauged by the Gini coefficient (Wagner et al., 2025). Higher inequality can lead states to have more social tension, less trust, and economic frustrations that might be a source of an increase in crime. This subject can enable me to discuss structural economic explanations of crime and not simply the policing strategies. B. Research Question What factors explain variation in violent crime rates across U.S. states? C. Why This is a Good Question This is a good research question since it tackles a significant public policy question, and it has more than one way of explanation. Crime is a very controversial political subject, and the causes of crime offer an implication on budgeting, social programs, and law enforcement policy. I am intrigued by this subject due to its linking of the economic disparity and the social security that often takes the center stage in political debates. This question is relevant, as crime influences the social stability of the community, its economic development, and the quality of life in general. This study can contribute to the wider discussion of the problem of whether social welfare policies or policing strategies are more effective in reducing crime by answering the research question of whether income inequality contributes to violent crime rates. D. Variables Dependent Variable: Violent crime rate: the rate of reported violent crimes per 100,000 persons in the respective state. Independent Variable 1: Income inequality (Gini coefficient), which is the measure of the unfairness of income distribution within the state. Independent Variable 2: Poverty rate, which is a measure of the percentage of people who live below the federal poverty line.

Independent Variable 3: Police spending per capita, which is the measurement of the amount of money each state spends on law enforcement if this is in comparison with the population. E. Hypothesis I hypothesize that the more income inequality there is in the state, the more violent crimes there are in it. The independent variable in this hypothesis is income inequality, and the dependent variable is the violent crime rate. The causal process of this argument is that the inequality may contribute to the rise of relative deprivation and decrease social cohesion (Zhuang et al., 2025). When people feel that there are huge economic divergences between them and others, it can lead to frustration and resentment, and low confidence in institutions. These are conditions that may lead to criminal behavior or social instability. Police expenditure might prevent certain crime although structural inequality might be the source of some social strains that lead to increased rates of violent crime.

Results Section (Analysis and Assessment)

Audience: People who are interested in the results of your hypothesis tests. Assume the audience has

read the previous sections of your paper. Assume they only know as much about your topic as you

have explained so far, including what your hypotheses are and what variables you are using. Consider

two distinct types of readers: one type that understands all the material on statistics and data analysis,

and another who does not know what all the technical details mean but wants to understand the

basics of your results. The first type of reader should get a detailed picture of your analyses, while the

second type should be able to decipher the basics of whether your hypotheses were supported and

why.

Purpose: The goal of this section is to provide sufficient detail for the reader to be able to understand

the results of your data analyses. Most readers use this section to determine what your findings are

and see if you found support for your hypotheses. A few will use it to critically examine whether you

used appropriate tests and found valid results.

Style: The writing should be formal, focused on explaining the results of hypothesis tests. This section

should be specific and have some technical language. Write to help your reader understand how you

tested each hypothesis and what you found. You may write in first person or third person based on

your preference. It is natural for the writing in this section to be repetitive, as you will be giving similar

information for each of your hypotheses. You do not need to revise your content or paragraph

structure to avoid repetition. This section does not usually use any sources, but if you refer to any

information from a source, make sure you properly cite it. Make sure you leave time to proofread and

edit before submitting.

What to include: Summarize and interpret the results of your data analysis in paragraph form. Include

the following components.

1. Report the result of each of your bivariate analyses. Each of your three (or more) hypotheses

should have a test of the bivariate relationship (with one IV and one DV only). Depending on your

variables, you can use: a correlation without; an independent-samples t-test; or a bivariate linear

regression analysis. You can use a different type of analysis for different hypotheses, as

appropriate, or use the same method for all three (if the variables fit that method). The details you

should include for each type of analysis are explained below in the worksheet portion of the

assignment. Each analysis should include the SPSS tables and describe the results in a paragraph for

each hypothesis.

2. Report the result from your multiple regression. In one or more paragraphs, explain the results of

all three hypotheses tested simultaneously. In your response, include the following: Report the

intercept (a) of the regression line and interpret it in the context of the regression model as a

whole. Interpret the effect of each IV in the context of the variables, including the value of the

slope (b) in the sentence. Explain whether each relationship is significant based on the t-score

and/or p-value for each slope. Based on the direction of the slope and the significance, indicate

whether each hypothesis is supported based on these results. Finally, state the R2 of the model and

describe how well the model predicts the dependent variable. *Remember: each hypothesis can be

supported even if there are also significant relationships involving the other independent variables.

Even a weak relationship supports a hypothesis if it is in the direction expected and is significant.

3. Findings: Summarize your findings overall in minimally technical language: In a paragraph, analyze

whether each hypothesis was supported based on the data analysis in both bivariate and

multivariate tests for all three hypotheses, including the results from both the bivariate and

multivariate tests. *Here, you do not need to include the specific values of the slopes or

significance tests.* In your explanation, include whether the results were in the direction you

expected and if the results were significant. Clarify whether the results were consistent in all tests,

or if the results differed in the bivariate and the multivariate tests. Was there stronger support for

one hypothesis over the others, based on the strength and magnitude of each relationship?

Hypothesis Testing Worksheet

You should test each hypothesis with one of the methods provided: correlation, independent samples

t-test, OR bivariate regression. Then, everyone will use multiple regression to test all the hypotheses

together. Use this worksheet to decide which test will work and put together the information needed

for that test.

Correlation: Each analysis should include only one independent variable and your dependent variable.

Use this worksheet to write down the specific details you will then write into a paragraph. Variables:

should be used when the variables are ordinal or interval level and none of the variables are dummy

variables.

A. Include the SPSS output in your assignment labeled “Correlations”

B. What is the correlation value?

C. What is the p-value for the correlation?

D. Was your hypothesis supported based on these results?

Independent Samples T-Test: Each analysis should include only one independent variable and your

dependent variable. Use this worksheet to write down the specific details you will then write into a

paragraph. Variables: should be used when the IV is a dummy variable and the DV is an ordinal or

interval variable.

A. Include the SPSS output in your assignment, including the box labeled “Group Statistics”

AND the table for “Independent Samples Test”

B. What is the mean value of the DV for each category of the IV?

C. What is the mean difference, “Mean Diff”?

D. What is the t-score, “t”?

E. What is the p-value, “Sig. (2-tailed)”?

F. Was your hypothesis supported based on these results?

Bivariate Regression: Each analysis should include only one independent variable and your dependent

variable. Use this worksheet to write down the specific details you will then write into a paragraph.

Video tutorial: running the regression: https://youtu.be/ubZT2Fl2UkQ Part 2, interpreting the results:

https://youtu.be/altU9ZVb49s. Variables: should be used when the variables are ordinal or interval

level and none of the variables are dummy variables.

A. Include the SPSS output in your assignment, including the box labeled “Coefficients” and the

box labeled “Model Summary.”

B. What is the value of the intercept (a) (indicated in SPSS as the Constant)?

C. What is the slope coefficient (b)?

D. What is the t-score for the slope coefficient (b)?

E. What is the p-value for the slope coefficient (b)?

F. What is the R2 of this regression line?

G. Was your hypothesis supported based on these results?

Multiple Regression: Run a multiple regression with all three independent variables included and the

same DV. Use this worksheet to write down the specific details you will then write into a paragraph.

A. Include the SPSS output in your assignment, including the box labeled “Coefficients” and the

box labeled “Model Summary.”

B. What is the value of the intercept (a) of the regression line?

C. What is the slope coefficient (b) for each IV?

a. IV1:

b. IV2:

c. IV3:

D. Is each slope significant? Provide the t-score and p-value for the slope of each IV.

a. IV1:

b. IV2:

c. IV3:

E. What is the R2 of this regression line?

Criteria Excellent 90 - 100%

Satisfactory 75 - 90%

Unsatisfactory 60 - 75%

Poor 0 - 60%

Bivariate Hypothesis Tests 30% of total grade

Complete and understandable description of the results of a test for each hypothesis. Includes relevant statistics (correlation, regression coefficients, significance)

Includes some details but is incomplete or unclear in places. Uses an inappropriate test or issues with interpretation.

Major issues with missing key information for hypotheses tests or missing one or more hypotheses. Major misunderstanding of results

Incomplete or lacking an understanding

Multivariate Regression 30% of total grade

Complete and understandable description of the results of a multiple regression. Includes relevant statistics (intercept, slopes, significance, r-squared)

Some missing details. Mostly complete but some areas of unclear description or misinterpretation.

Major issues describing the results or setup of the regression. Needs substantial revision or missing important information.

Incomplete or lacking an understanding

Tables 20% of total grade

Includes all tables/charts. All tables are properly done.

Mostly complete tables with minor errors or missing parts

Missing tables or major issues with some tables

Does not meet the requirements of the assignment

Findings 20% of total grade

Clear, complete, and accurate summary of results. All hypotheses included.

Good summary of results with minor errors or missing details.

Incomplete or confusing summary of findings. Major errors or missing information.

Missing section or multiple major errors.