As what can be seen from the data, the numbers and statistics show that there is some correlations to suggest that one influences the other. As the bar graphs show, there is a trend of the percentages matching and growing together, although not exact. However, the sum of both categories is also different so this data does not fully represent the accurate total. Based on the data, there does seem to be indications that feeling like people's public officials don't listen to them can be related to how important it is for an individual. The more an individual feels like their official will listen to them, the more important politics will be to them. 

Work Cited
Benenson, J., & Bergom, I. (2019). Voter participation, socioeconomic status, and institutional contexts in higher education. Review of Higher Education, 42(4), 1665–1688. https://doi.org/10.1353/rhe.2019.0079

Frisco, M. L., Muller, C., & Dodson, K. (2004). Participation in voluntary youth-serving associations and early adult voting behavior. Social Science Quarterly, 85(3), 660–676. https://doi.org/10.1111/j.0038-4941.2004.00238.x
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Author: Kaitlin Victorino 

Although there's much data spread across the three graphs, we can analyze how voting barriers have had an influence on different race groups in America. We can see how those who are white, encounter less voting barriers and turnout at a higher rate to vote. However, the data provided cannot accurately say that these statements regarding non-white races is certain due to a lack of equal participation in the survey. 

Author: Isabella Arellano
 
Literature Review:
Political equality is central to contemporary understandings of democracy as citizens should not only have the right to participate in collective decision making but also the selection of their representatives. However, in recent years political participation has decreased in western democracies which have roughly coincided with a rise in economic inequality. The relation among the economic inequality and voter turnout has been controversial in studies and reasons for this is because inequality is argued to be a relational concept as it depends on how it is measured. Measuring the impact of spatial inequality, or the unequal distribution of resources across areas (Bartle 2017). 
 
Analyzing why individuals do not participate politically, people often responded with three different answers - they can't, they don't want to, or no one asked them too. The response that they cant suggests that it concerns resources; They can't participate because they don't have the time, the money, or the civic skills. The issue of access to resources is more concerning than the answer that they don't want to which is concluded to be by personal choice that they would rather be devoted to private over public pursuit while the answer that no one asked them to is the consequence of resource constraints that make it difficult for those who are politically interested and engaged to take part in political life then we are more concerned about access to resources (Brady 1995). Access to resources is concerning particularly more so with income as its often the case that individuals do want to participate politically but simply cannot afford to. 
 
The two prime resources concerning investment in political participation are time and money. Time can be described in relation to political participation in a multitude of ways including working in a campaign, writing a letter to a public official, attending a community meeting, etc. The way it is measured in this study is in “free” time which is after hours worked for pay, hours spent doing essential daily tasks, studying or going to school, and sleeping. Money can be donated to candidates, parties, or innumerable political organizations or causes although it is more constrained and differences among individuals can be larger. Time is constrained in the way that it is distributed differently and cannot be put into the bank whereas money can be accumulated for later use (Brady 1995). 
 
Importance of representing every demographic in politics:
These findings are relevant to our society as it suggests that certain populations and therefore viewpoints are underrepresented in politics. Not having certain viewpoints represented in our political system is problematic to a society as it takes away the opportunity to operate optimally as not everyone’s needs are met and therefore served, usually an essential to be able to advance in the most convenient way possible.

Hypothesis:
Null hypothesis: There is no correlation between race and feelings of financial stress to voter turnout. 
Alternative hypothesis: There is a correlation between race and feelings of financial stress to voter turnout. 

Methodology:
Collecting information on whether or not minority students have a lower turnout, I explored whether or not there was a difference in means between race and feelings of financial stress, and whether or not students planned to vote and feelings of financial stress. Casual mechanisms that may also be able to explain my hypothesis includes racial inequality which can entail unequal access to resources such as jobs and acceptance into schools, and in turn can affect civic skills/participation. 

The study sampled 175 students at Fort Lewis College through a survey which asked a wide array of questions that are significant to political participation, although the specific codes I used included [FinStress] which was reported on a scale of 0-6 with 0 = strongly disagree and 6 = strongly agree, and the [Vote2020YN] which asked students if they plan to vote with 1 = Yes and 0 = no, and race which asked what race best describes the person. 

Results:
The results among both difference in means varied. Figure 1 shows that students who are black report a wider array of feelings of financial stress while every other race varies much less although only 2 black students were surveyed. In figure 2, both the error bars overlap which show us that there is no significance between financial stress among those who did not vote and those who did, while it is also important to keep in mind that there were only 13 individuals that did not plan to vote. 

The significance between financial stress and race was primarily measured through looking at the error bar mean however finding the correct numbers through tests was difficult to complete as race was nominal data that would not work on a correlation test in SPSS whichsignificance between financial stress and whether or not the person voted was .280 .28% which indicates that it is not significant enough to reject the null hypothesis. 

Figure 1:

Figure 2:

Figure 3:

​Conclusion:
There was not enough statistical evidence to reject either null hypothesis, therefore financial stress does not affect the voter turnout of racial minorities. Limitations to this study include sampling a bigger population as only 175 people were surveyed, and the piece of data that appears to be significant would be how many black students feel financial stress although only 2 answered that question, as well as the amount of students that did not vote visually looks significant although only 13 students answered that they would not vote.

Citations:

• Bartle, John, et al. “The Local Roots of the Participation Gap: Inequality and Voter Turnout.” Electoral Studies, vol. 48, Aug. 2017, pp. 30–44. EBSCOhost, doi:10.1016/j.electstud.2017.05.004.
• Henry E. Brady, et al. “Beyond Ses: A Resource Model of Political Participation.” The American Political Science Review, vol. 89, no. 2, 1995, p. 271. EBSCOhost, doi:10.2307/2082425.

​Hypotheses and Motivation:
In our group, we analyzed voter suppression and disenfranchisement among racial minority groups. Within voter suppression and disenfranchisement, voter identification (ID) requirements and laws have been a prevalent factor that has been affecting racial minority groups, when compared to white individuals. For this reason, I created two hypotheses to analyze whether racial minority students have been impacted by voter identification requirements. The null hypothesis is voter ID requirements do not disproportionately impact racial minority students, when compared to white students. The alternative hypothesis is voter ID requirements disproportionately impact racial minority students, when compared to white students.
One study that is linked to this hypothesis is by Zoltan Hajnal, Nazita Lajevardi, and Lindsay Nielson who focused on the relationship between voter identification laws and the suppression of minority votes (Hajnal, Lajevardi, and Nielson, 2017). Within their study, they utilized voting data from the Cooperative Congressional Election Study and compared data between states that obtain strict voter ID laws to states that have less strict voter ID laws or have barely implemented voter ID laws. Hajnal et al., identify gaps in voting turnout between minority groups and white individuals. Another study was conducted by Ben Pryor, Rebekah Herrick, and James A. Davis who examined “the effects of strict voter identification (ID) laws on minority voters” (Pryor, Herrick, and Davis, 2019). Pryor, Herrick and Davis attempted to replicate the work of Hajnal, Lajevardi, and Nielson and utilized data from the Current Population Survey (CPS) Voting and Registration Supplement (Pryor, Herrick, and Davis, 2019). Ultimately, both studies conclude that we still are unaware of which variable contributes the most to understanding voter suppression. Likewise, they both emphasize that there are many underlying variables to evaluate whether voter ID laws disproportionately affect racial minority groups.
Although there has been advancement in voting rights, such as the Voting Rights Act of 1965 that prohibited discriminatory voting tactics, voter suppression and disenfranchisement continues to coexist. Therefore, this hypothesis test is crucial in analyzing the component of race and how it plays a role within election systems and voting abilities of racial minority groups in order to help readers understand the equity and opportunity gap within society. 

Description of Concepts, Data and Measurement:
The variables incorporated in this analysis are race and voter identification requirements. The independent variable for this analysis is race. Race is an imperative variable when analyzing voter suppression and voter ID requirements. Throughout history, the U.S. election system has unfairly impacted racial minority groups. Minority voter disenfranchisement is not limited to voter ID laws, it is also includes voter caging, lying flyers, reprehensible billboards, felon disenfranchisement, voter purges, voting times and methods, etc. (Parker et al. 2018). Within this study, race was categorized into seven categories, which included white, African American, Native American, Indigenous, or Alaska Native, Asian, Hispanic or Latinx, multiple races or ethnicities, and other. For this study, I recoded the variable of [Race] to [Race2] and separated it into two categories, which were white (0) and non-white (1). I recoded these variables to evaluate whether racial minority students were disproportionately impacted by the variable [VoteID], when compared to white students.
The dependent variable is [VoteID], which was based upon whether an individual had to provide a required form of identification to vote. Similar to the independent variable, I recoded the variable of [VoteID] to [VoteID2] and separated it into two different categories. The first category is an individual did not have to show a voter ID (0) and an individual did have to show a voter ID (1). The required form of voter ID included options, such as driver’s license, state ID card, tribal ID card, military ID, student ID, and social security card/number. These options are based upon the state that an individual is registered to vote in and whether their state has enacted voter ID laws. Voter ID laws are laws that require an individual to provide a form of identification to vote and cast their ballots during an election. The common types of voter identification requirements include a driver’s license, birth certificate, passport, utility bill, property tax statement, etc. (Pryor, Herrick, and Davis 2019). These requirements vary throughout each state. Moreover, the causal mechanism within this analysis is that certain racial minority groups lack the ability to obtain a voter ID due to their physical address, lack of necessary documentation, such as a birth certificate, etc. (Gaskins, Iyer, 2012). 

Presentation of Analysis and Results:
Figure 1:
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For this study, I conducted a difference of means test/independence sample T-Test. After conducting the test, the results varied. Figure 1 shows that about 64% of white individuals voted and about 77% of non-white individuals voted. In Figure 2, the significance values were 0.185 and 0.18, which illustrates that there is about an 18% chance of committing a Type I Error. A Type I error is when you reject the null hypothesis, when in reality, you should have retained it. Therefore, you are claiming that you found a difference/relationship, when really, there was no difference/relationship. However, since the significance value is not similar to a statistical significance found in peer review studies that obtain values of .05, this test is suggestive in which it illustrates that there is something real occurring in the context between voter turnout of white and non-white individuals. 
​Figure 3 shows that there is a roughly equal number of white and non-white individuals who had to show some form of voter ID requirements in order to vote. Also, there were fewer non-white individuals who were not required to show their voter ID, when compared to non-white individuals. Therefore, this figure illustrates that non-white individuals within our study were more likely to show their voter ID when they attempted to vote. As a result, we see that non-white individuals had a higher voter turnout, although they faced more voter ID requirements. Ultimately, voter ID requirements play a substantial role in understanding voter suppression and disenfranchisement of racial minority groups.

Works Cited:
Gaskins, Keesha and Sundeep Iyer. 2012. "The Challenge of Obtaining Voter Identification." Brennan Center For Justice. https://www.brennancenter.org/our-work/research-reports/challenge-obtaining-voter-identification. 

Hajnal, Zoltan, Nazita Lajevardi, and Lindsay Nielson. 2017. “Voter Identification Laws and the Suppression of Minority Votes.” Journal of Politics 79 (2): 363–79. https://doi.org/10.1086/688343.

Parker, Keith, Komanduri Murty, A. Lakshminath, and Dora Tilles. 2018. “Using Microaggression Theory to Examine U.S. Voter Suppression Tactics.” Negro Educational Review 69 (1–4): 101-23.

Pryor, Ben, Rebekah Herrick, and James A. Davis. 2019. “Voter Id Laws: The Disenfranchisement of Minority Voters?” Political Science Quarterly 134 (1): 63–84. https://doi.org/10.1002/polq.12868.