This was a research presentation for my quantitative research methods class. I generated a research question, selected variables from a national dataset, and used SPSS to analyze my data.

1. Salaried
Discrimination
An Analysis of Perceived Racism and Income Level

2. Introduction
 Although we once believed that race was biological, we have since
realized that race is actually a social construct (Andreasen,2000).
 There are still immense issues with racial inequality even though
we now recognized that race is socially constructed rather than
genetically based.
 In today’s society, many individuals would like to believe that we
live in a post-racial era, however that is just not the case.

3. Methods
 My colleagues and I participated in a national a cross-sectional
study utilizing Behavioral Risk Factor Surveillance System (BRFSS)
data obtained by the Center for Disease Control and Prevention
(CDC). We specifically focused on the relationship between
reactions to race in the workplace and income level.
 IRB Approved Research
 Funding Source: The CDC
 Data Source: The Behavioral Risk Factor Surveillance System
 Timeline: August 1st
2014-August 1st
2015

4. Results
Value Degrees of
Freedom
Asymp. Sig.
(2-sided)
Pearson Chi-Square 10.25 6 .114
Problem: Our research team
analyzed whether perceived racism
and income were associated with
one another.
Test: A Chi-square test of independence was calculated comparing the two income
ranges with perceived racism in the workplace. A non-significant interaction was
found (𝜒² (6)= 10.25, p> 0.05). There was no difference in how an individual perceived
racism based on their income.
Value Approx. Sig
Pearson’s R -.038 .114
A Pearson Correlation test of independence was calculated to determine if
perceived racism was independent of income level. A weak negative interaction
was found (r= -.038, p> 0.05). Perceived racism is not related to income.
Step -2 Log Likelihood Cox & Snell R
Square
Nagelkerke R
Square
1 160.6 .001 .002
Logistic regression was calculated to determine the strength among variables.
The log likelihood value was incredibly large, suggesting that this particular
model was a poor fit. In this case a Nagelkerke R² of .002 (.2%) further indicates
that there is likely no relationship between the predictor and the prediction

5. Discussion
 Research Question: Is there an associated between perceived racism and
income level?
 My colleagues and I hypothesized that perceived racism and income would be
associated with one another. More specifically, we hypothesized that the
perception of racism in the workplace would decrease as income level
increased.
 After utilizing the Statistical Package for Social Sciences (SPSS) software to
analyze our data we discovered that there was no statistically significant
associates between perceived racism in the workplace and income level.
 Interpretation: We concluded that based on the complex and multifaceted
nature of racism other factors should be considered in addition to income.
Some other potential variables of interest include: occupation, geographic
location, and age.
 A large amount of literature regarding race focuses on the health impact that
racism can impose, as a future study we would like to analyze race, income,
and health outcomes.
 Limitations: Unfortunately because of our design time we cannot analyze this
particular behavior overtime. Another issue is that the timing of this particular
snapshot may not be actually be representative of the nation, it only speaks to
the specific time frame.
 Strengths: We had an immense amount of data because of the data was
nation wide. Our study was relatively inexpensive and a lot less time
consuming than a case-control study.

6. References
Andreasen, R. O. (2000). Race: Biological reality or social construct? Philosophy of Science,67(3), S653-S666.
doi:10.1086/392853

7. References
Andreasen, R. O. (2000). Race: Biological reality or social construct? Philosophy of Science,67(3), S653-S666.
doi:10.1086/392853