Political research/data

DataandMethodsSection.docx

Data and Methods Section

Audience: People who are interested in the details of the variables you use to test your hypotheses. Assume the audience has read your literature review and understands the basics of research design and measurement (e.g. they know what a sample size is and the definition of a median). Assume they are not familiar with your specific variables or research design and want to understand those details.

Purpose: The goal of this section is to provide sufficient detail for the reader to be able to critically analyze the quality of your data. You must give details on the research design and the measurement of each variable to be transparent about your data. If you wrote specific concept definitions or details about measurement in your literature review, you should move that material to this section instead.

Style: The writing should be formal, focused on explaining the sources of data, defining your variables, and explaining how they are measured. This section should be specific and have some technical language. Write to help your reader understand what each variable is and the distribution of the variable in your dataset. You may write in first person or third person based on your preference. Provide proper citations for the sources used, including for the variable definitions and sources of information on the research design and how variables are measured. Citations should be given in parenthetical form in your text and in full-length in a references page at the end of the document. I recommend using APA style citations, though any consistently used style is acceptable. You may use quotes from sources of the data to fill in parts of this but should explain as much as you can in your own words. Any use of others’ language without quotes will result in grade deductions, up to a 0 on the assignment for egregious copying of text. You may also NOT use AI to help you reword the text. Make sure you leave time to proofread and edit before submitting.

The section should include 4 different components. First, describe the overall research design. Then, describe three components of each variable. Describe the measurement details of the variable, descriptive statistics, and validity and/or reliability for each variable. Put all the information for each variable together. Use the attached worksheets to see what information you need to include, as different content is needed for survey data vs. aggregate data.

Research Design

Describe the research design of the data you are using. This section will include more information for those using survey data than those using aggregate data. See worksheet for details.

Variable Descriptions:

You should include all variables included in your hypotheses, at least 4 variables total (3 IVs and 1 DV). For each variable, include the following details:

A. Discuss your measurement plan

For each variable, define the concept the variable is trying to measure, then describe the variable you are using to measure this concept, giving a detailed operational definition of the variable. This definition should be detailed enough so that if someone wanted to gather data for this variable themselves, they would have a decent idea of how to do so. The type of details needed varies between survey and aggregate data. Refer to the appropriate worksheet for what information is required for your project.

B. Descriptive Statistics

Provide descriptive statistics for each of your variables. Include a table (frequency distribution) or chart (histogram) for each variable and a table with the relevant statistics for central tendency (mean, median) and dispersion (standard deviation, range, shape of distribution). Describe the distribution of each variable, referring to the tables as needed. You can include the tables in the text or include them all at the end. Number each table or chart and refer to it in the text where you discuss each. Number each table (i.e. “Table 2”) and refer to it in the text where you discuss it (i.e. “According to table 2, the mean is 5.7).

C. Reliability and Validity

Evaluate each of your variables in terms of the major types of validity and reliability. Each variable should include analysis of validity or reliability in some way, referring specifically to face validity, content validity, criterion-based validity, and reliability as it is appropriate. You must analyze the content validity for at least one variable. You should also discuss reliability of at least one variable. Be honest and self-critical. It is okay and expected to have imperfect variables and include some criticism of the measurements.

research1posc.docx

7

Economic and Social Factors Influencing Health and Crime Outcomes Across U.S. States

Sumaiya El-Amin

Towson University

Professor Oliver

Political Research

February 13th, 2026

Topic 1: Economic and Policy Factors Influencing Health Outcomes Across U.S. States

A. Topic Description

Among the topics that I may use to write my research paper is the difference in the health outcomes across the U.S. states and what factors can be used to explain it. The United States has a high level of disparity in health outcomes based on the location of the individual (Crimmins, 2025). Certain states are ranked higher in life expectancy, lower rates of preventable deaths, and overall better public health indicators, whereas others have always been ranked lower (Crimmins, 2025). Access to healthcare may be affected by policy decisions, including the adoption of Medicaid expansion by the state as part of the Affordable Care Act (Guth et al., 2020). Other socioeconomic forces, such as income, education levels, and healthcare expenditure, among others, are also important. The subject matter will enable me to investigate the interaction between economic resources and the decisions made by the state policy to influence the health of the population on a state level.

B. Research Question

What factors explain variation in overall health outcomes across U.S. states?

C. Why This is a Good Question

This is a good research question in that it can have various competing explanations as opposed to one particular policy being the sole cause of health disparities. Although Medicaid expansion can enhance access to healthcare, income, education, and state investment in healthcare systems can also play a huge role in determining health outcomes. This question is of interest to me because health inequality is a significant American political and social concern. Knowledge about determinants of variations in health outcomes may assist policy-makers in developing more efficient interventions. The relevance of this question lies in that it concerns the priorities of public spending, social inequality, and the impact of the government on facilitating well-being. It also has practical consequences for millions of Americans since their life expectancy and quality of life vary according to the location.

D. Variables

Dependent Variable: The general health, which will be determined by such indicators as the expectancy of life or the level of preventable deaths. This is an indicator of the general health condition of people in every state.

Independent Variable 1: Median household income, which is the economic resources of the households in a state. The increased income level can enable people to purchase quality, nutritious food, housing, and healthcare services.

Independent Variable 2: Medicaid expansion status, which is an indicator of whether a state implemented Medicaid expansion based on the Affordable Care Act. Growth enhances the eligibility of low-income adults to public health insurance.

Independent Variable 3: State healthcare spending per capita, which is the amount a state spends on healthcare services and public health systems for each resident.

E. Hypothesis

I suppose that the overall health outcomes of states with larger median household income will be better than those with lower median household income. The independent variable in this hypothesis is the median household income, and the dependent variable is the overall health outcomes. The cause and effect of this argument is that increased income level gives people more access to health-promoting resources, e.g., nutritious food, stable housing, preventive health care, and reduced stress levels. As much as the expansion of Medicaid could result in the rise of insurance coverage, income has an influence on a wider spectrum of social determinants of health. Economic resources will tend to affect overall health outcomes more directly and reliably than policy adoption itself.

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.

References

Crimmins, E. M. (2025). Life expectancy and health expectancy in the twenty-first century: The unthinkable, the inconceivable, and the unknowable. Demography. https://doi.org/10.1215/00703370-12185960

Guth, M., Garfield, R., & Rudowitz, R. (2020). The effects of Medicaid expansion under the ACA: Studies from January 2014 to January 2020 | KFF. KFF. https://www.kff.org/medicaid/the-effects-of-medicaid-expansion-under-the-aca-updated-findings-from-a-literature-review/

Ulmer, J. T., Harris, C. T., & Steffensmeier, D. (2012). Racial and ethnic disparities in structural disadvantage and crime: White, Black, and Hispanic comparisons*. Social Science Quarterly, 93(3), 799–819. https://doi.org/10.1111/j.1540-6237.2012.00868.x

Wagner, D. A., Nair, T., Thapa, A., & Kumar, A. (2025). The Gini learning index: A new framework to measure learning inequality across contexts. International Journal of Educational Development, 119, 103433. https://doi.org/10.1016/j.ijedudev.2025.103433

Zhuang, Z., Xie, X., Huang, L., Yan, J., Cheng, S., & Xu, A. (2025). The impact of relative deprivation on mental health among middle-aged and older adults in China: A multiple chain mediation model. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-20182-8

DataandMethodsSection.docx

Data and Methods Section

Audience: People who are interested in the details of the variables you use to test your hypotheses. Assume the audience has read your literature review and understands the basics of research design and measurement (e.g. they know what a sample size is and the definition of a median). Assume they are not familiar with your specific variables or research design and want to understand those details.

Purpose: The goal of this section is to provide sufficient detail for the reader to be able to critically analyze the quality of your data. You must give details on the research design and the measurement of each variable to be transparent about your data. If you wrote specific concept definitions or details about measurement in your literature review, you should move that material to this section instead.

Style: The writing should be formal, focused on explaining the sources of data, defining your variables, and explaining how they are measured. This section should be specific and have some technical language. Write to help your reader understand what each variable is and the distribution of the variable in your dataset. You may write in first person or third person based on your preference. Provide proper citations for the sources used, including for the variable definitions and sources of information on the research design and how variables are measured. Citations should be given in parenthetical form in your text and in full-length in a references page at the end of the document. I recommend using APA style citations, though any consistently used style is acceptable. You may use quotes from sources of the data to fill in parts of this but should explain as much as you can in your own words. Any use of others’ language without quotes will result in grade deductions, up to a 0 on the assignment for egregious copying of text. You may also NOT use AI to help you reword the text. Make sure you leave time to proofread and edit before submitting.

The section should include 4 different components. First, describe the overall research design. Then, describe three components of each variable. Describe the measurement details of the variable, descriptive statistics, and validity and/or reliability for each variable. Put all the information for each variable together. Use the attached worksheets to see what information you need to include, as different content is needed for survey data vs. aggregate data.

Research Design

Describe the research design of the data you are using. This section will include more information for those using survey data than those using aggregate data. See worksheet for details.

Variable Descriptions:

You should include all variables included in your hypotheses, at least 4 variables total (3 IVs and 1 DV). For each variable, include the following details:

A. Discuss your measurement plan

For each variable, define the concept the variable is trying to measure, then describe the variable you are using to measure this concept, giving a detailed operational definition of the variable. This definition should be detailed enough so that if someone wanted to gather data for this variable themselves, they would have a decent idea of how to do so. The type of details needed varies between survey and aggregate data. Refer to the appropriate worksheet for what information is required for your project.

B. Descriptive Statistics

Provide descriptive statistics for each of your variables. Include a table (frequency distribution) or chart (histogram) for each variable and a table with the relevant statistics for central tendency (mean, median) and dispersion (standard deviation, range, shape of distribution). Describe the distribution of each variable, referring to the tables as needed. You can include the tables in the text or include them all at the end. Number each table or chart and refer to it in the text where you discuss each. Number each table (i.e. “Table 2”) and refer to it in the text where you discuss it (i.e. “According to table 2, the mean is 5.7).

C. Reliability and Validity

Evaluate each of your variables in terms of the major types of validity and reliability. Each variable should include analysis of validity or reliability in some way, referring specifically to face validity, content validity, criterion-based validity, and reliability as it is appropriate. You must analyze the content validity for at least one variable. You should also discuss reliability of at least one variable. Be honest and self-critical. It is okay and expected to have imperfect variables and include some criticism of the measurements.

research1posc.docx

7

Economic and Social Factors Influencing Health and Crime Outcomes Across U.S. States

Sumaiya El-Amin

Towson University

Professor Oliver

Political Research

February 13th, 2026

Topic 1: Economic and Policy Factors Influencing Health Outcomes Across U.S. States

A. Topic Description

Among the topics that I may use to write my research paper is the difference in the health outcomes across the U.S. states and what factors can be used to explain it. The United States has a high level of disparity in health outcomes based on the location of the individual (Crimmins, 2025). Certain states are ranked higher in life expectancy, lower rates of preventable deaths, and overall better public health indicators, whereas others have always been ranked lower (Crimmins, 2025). Access to healthcare may be affected by policy decisions, including the adoption of Medicaid expansion by the state as part of the Affordable Care Act (Guth et al., 2020). Other socioeconomic forces, such as income, education levels, and healthcare expenditure, among others, are also important. The subject matter will enable me to investigate the interaction between economic resources and the decisions made by the state policy to influence the health of the population on a state level.

B. Research Question

What factors explain variation in overall health outcomes across U.S. states?

C. Why This is a Good Question

This is a good research question in that it can have various competing explanations as opposed to one particular policy being the sole cause of health disparities. Although Medicaid expansion can enhance access to healthcare, income, education, and state investment in healthcare systems can also play a huge role in determining health outcomes. This question is of interest to me because health inequality is a significant American political and social concern. Knowledge about determinants of variations in health outcomes may assist policy-makers in developing more efficient interventions. The relevance of this question lies in that it concerns the priorities of public spending, social inequality, and the impact of the government on facilitating well-being. It also has practical consequences for millions of Americans since their life expectancy and quality of life vary according to the location.

D. Variables

Dependent Variable: The general health, which will be determined by such indicators as the expectancy of life or the level of preventable deaths. This is an indicator of the general health condition of people in every state.

Independent Variable 1: Median household income, which is the economic resources of the households in a state. The increased income level can enable people to purchase quality, nutritious food, housing, and healthcare services.

Independent Variable 2: Medicaid expansion status, which is an indicator of whether a state implemented Medicaid expansion based on the Affordable Care Act. Growth enhances the eligibility of low-income adults to public health insurance.

Independent Variable 3: State healthcare spending per capita, which is the amount a state spends on healthcare services and public health systems for each resident.

E. Hypothesis

I suppose that the overall health outcomes of states with larger median household income will be better than those with lower median household income. The independent variable in this hypothesis is the median household income, and the dependent variable is the overall health outcomes. The cause and effect of this argument is that increased income level gives people more access to health-promoting resources, e.g., nutritious food, stable housing, preventive health care, and reduced stress levels. As much as the expansion of Medicaid could result in the rise of insurance coverage, income has an influence on a wider spectrum of social determinants of health. Economic resources will tend to affect overall health outcomes more directly and reliably than policy adoption itself.

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.

References

Crimmins, E. M. (2025). Life expectancy and health expectancy in the twenty-first century: The unthinkable, the inconceivable, and the unknowable. Demography. https://doi.org/10.1215/00703370-12185960

Guth, M., Garfield, R., & Rudowitz, R. (2020). The effects of Medicaid expansion under the ACA: Studies from January 2014 to January 2020 | KFF. KFF. https://www.kff.org/medicaid/the-effects-of-medicaid-expansion-under-the-aca-updated-findings-from-a-literature-review/

Ulmer, J. T., Harris, C. T., & Steffensmeier, D. (2012). Racial and ethnic disparities in structural disadvantage and crime: White, Black, and Hispanic comparisons*. Social Science Quarterly, 93(3), 799–819. https://doi.org/10.1111/j.1540-6237.2012.00868.x

Wagner, D. A., Nair, T., Thapa, A., & Kumar, A. (2025). The Gini learning index: A new framework to measure learning inequality across contexts. International Journal of Educational Development, 119, 103433. https://doi.org/10.1016/j.ijedudev.2025.103433

Zhuang, Z., Xie, X., Huang, L., Yan, J., Cheng, S., & Xu, A. (2025). The impact of relative deprivation on mental health among middle-aged and older adults in China: A multiple chain mediation model. Scientific Reports, 15(1). https://doi.org/10.1038/s41598-025-20182-8

DataandMethodsSection.docx

research1posc.docx

DataandMethodsSection.docx

Data and Methods Section

Research Design

Variable Descriptions:

A. Discuss your measurement plan

B. Descriptive Statistics

C. Reliability and Validity

research1posc.docx

Economic and Social Factors Influencing Health and Crime Outcomes Across U.S. States

Topic 1: Economic and Policy Factors Influencing Health Outcomes Across U.S. States

A. Topic Description

B. Research Question

C. Why This is a Good Question

D. Variables

E. Hypothesis

Topic 2: Income Inequality and Violent Crime Rates Across U.S. States

A. Topic Description

B. Research Question

C. Why This is a Good Question

D. Variables

E. Hypothesis

References

DataandMethodsSection.docx

Data and Methods Section

Research Design

Variable Descriptions:

A. Discuss your measurement plan

B. Descriptive Statistics

C. Reliability and Validity

Political reseaech