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Hypothesis results **files (3)** – ## Document1.pdf – ## _IncomeInequalityandViolentCrimeRatesAcrossU.pdf – ## ResultsSection.pdf **## Document1.pdf** Results Results **## _IncomeInequalityandViolentCrimeRatesAcrossU.pdf** Topic 2: Income Inequality and Violent Crime Rates Across U.S. States A. To…
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Hypothesis results
**files (3)**
– ## Document1.pdf
– ## _IncomeInequalityandViolentCrimeRatesAcrossU.pdf
– ## ResultsSection.pdf
**## Document1.pdf**
Results
Results
**## _IncomeInequalityandViolentCrimeRatesAcrossU.pdf**
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.
**## ResultsSection.pdf**
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?
[https://youtu.be/altU9ZVb49s](https://youtu.be/altU9ZVb49s)
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.
**## ResultsSection.pdf**
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?
[https://youtu.be/altU9ZVb49s](https://youtu.be/altU9ZVb49s)
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.
**## Document1.pdf**
Results
Results
**## _IncomeInequalityandViolentCrimeRatesAcrossU.pdf**
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.
**## ResultsSection.pdf**
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?
[https://youtu.be/altU9ZVb49s](https://youtu.be/altU9ZVb49s)
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.
**## Document1.pdf**
Results
Results
**## _IncomeInequalityandViolentCrimeRatesAcrossU.pdf**
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.
**## ResultsSection.pdf**
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?
[https://youtu.be/altU9ZVb49s](https://youtu.be/altU9ZVb49s)
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.
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