One of the most crucial components of this course is developing a research project from conceptualization to completion. Throughout the class, you created a research study based on publicly available data from the General Social Survey (GSS). You chose data which were representative of your interests and satisfied your research question and hypotheses. The Final Project: Guide to Completing the Research Study is where you pull together the research you've been working on the first six weeks of class.
Instructions:
Complete the following assignment by filling all requested information into the worksheet. You will need to utilize SPSS and the GSS data set provided in class to complete it. Use a different, but legible, color font for your responses. This assignment is intended to help you complete the writing of a quantitative research summary/article, with particular emphasis on the Findings and Conclusion sections.
CO1: Describe and apply the concepts and logic of elementary statistics.
CO2: Conduct statistical analysis in SPSS (Statistical Package for the Social Sciences).
CO3: Compare and contrast different types of data and the statistics that can be used to analyze them
CO4: Examine the differences between descriptive and inferential statistics and their use in the social sciences.
CO5: Complete and interpret descriptive and inferential statistical data analysis.
CO6: Develop a research project from conceptualizing a research problem and develop a number of complementary design, measurement, and data collection approaches to bring evidence to bear on the problem.
CO7: Form critical interpretations of quantitative research literature in sociology and other social sciences, critically evaluating the quality of research design and evidence in published social research.
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SOCI332 Assignment: Final Project – Guide to Completing the Research Study
Complete the following assignment by filling in all requested information. You will need to utilize SPSS and the GSS dataset provided in class to complete it. Information should be based on the variables you chose and analyzed in Weeks 1-6. Use a different, but legible, color font for your responses. This assignment is intended to help you complete the writing of a quantitative research article, with particular emphasis on the Findings and Conclusion sections.
The assignment is to be completed and submitted no later than the Sunday of Week 7 by 11:55pm ET. It is worth 100 points.
(A) Introduction: Write an introduction to your research study in 1-2 paragraphs. Be sure to include a brief statement of current research on your topic (with an in-text citation of a source), a description of your research topic, why you chose the topic, what you hoped to learn from the topic, your research question, and your broad hypothesis.
(B) Literature Review: Write a 3-5 paragraph lit review (review of studies on your topic) using more than three sources, at least two of them being research studies in peer-reviewed journal articles.
(C) Methods/Dataset: In one paragraph, describe the GSS dataset.
(D) Methods/Variables: In one paragraph, discuss why you chose the specific independent and dependent variables for your analyses. Include the names of the variables, the level of measurement, the questions asked in the survey, and the response choices for each.
(E) Methods/Variable information: Copy and paste your frequency tables and descriptive statistics for each variable. Include your charts as well (histogram, bar, or pie). Provide a summary/explanation of what these tables/charts tell us about your variables:
(F) Findings: Copy & Paste corrected analyses from Weeks 3-6, i.e., Crosstabs, Measures of Association, Tests of Significance. Include the five steps of hypothesis testing.
(G) Findings: Explain what the analyses displayed above tell us about the relationships between the variables in the study.
(H) Conclusions: Explain how the findings contribute to the study of your topic. What did you learn? What other variables need to be explored? What further research on your topic could be pursued in the future?
References: Include full APA citations of all sources used. List them in alphabetical order by the author’s last name. Use hanging indentation (Line spacing options – Indention – Special – Hanging). Don’t forget to cite the GSS dataset (citation is listed in Week 1 Lessons).
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1. Does serving in the armed forces increase the likelihood of substance abuse? is my topic of discussion. I want to know why people take substances first and then become addicted, which is why I want to do this research. There are many reasons why people abuse substances, but what if one of those reasons is their time spent in the military? VETYEARS and EVIDU are the two variables I selected from the GSS data. The independent variable, VETYEARS, stands for years spent in the armed forces. The dependent variable, EVIDU, is a representation of R's total number of injections.
Independent variable (VETYEARS):
Dependent variable (EVIDU):
Explanation of the Output
The number of respondents who fit into each answer group for the survey question is indicated in the frequency column. Of the 2,348 respondents who completed the poll, 1,391 had legitimate responses, of which 41 were "Yes" and 1,350 were "No." The other responses fell into the invalid "IAP" and "NA" categories. The total proportion of respondents for each category is displayed in the percent column. The "Yes" receives a 2.9% and the "No" receives a 97.1% in the valid percent column, which only displays the percentage of each category out of 1,391 valid replies. From top to bottom in the table, the percentages of all the acceptable categories are added up in the cumulative percent column, which totals 100%.
Pie chart – independent variable VETYEARS:
The percentage of each valid response category for the number of years in the armed forces is shown on each slide of this pie chart, totaling 100%. It can be seen from the blue slide (89.47% of the pie) that the majority of survey participants had no military experience. 2.35% of responders who served for less than two years are depicted in the green slice. 4.31% of responders who served for two to four years are depicted in the red slice. 3.88% of respondents, as indicated by the orange slice, had more than four years of military service.
Pie chart – dependent variable EVIDU:
The percentage of each appropriate answer category for medications administered is shown on each slide of this pie chart, totaling 100%. The green slide displays the 97.05% of participants who stated they have never used an injection device. The percentage of respondents who acknowledged using injectable medications recreationally is displayed in the blue slice at 2.95%.
Independent variable (VETYEARS):
The average of the distribution of years spent in the military forces is shown by the central tendency measures. We just need to add together all of the VETYEARS values—both valid and missing and divide the total by the number of values to find the mean. The data indicates that the average number of years that respondents were in the armed forces was 0.23. When values are ordered from smallest to largest, the midway value is called the median. Since there is no median for years of service in this instance, it is.00.
The number that appears the most frequently in the data set is the mode. The mode in the table, which is 0, shows that the majority of respondents did not serve in the military. The dispersion metric shows the VETYEARS variation. Each number in the data set's variance is a measurement of its separation from the mean. The table's variance value is really low, indicating that the data points are in close proximity to both the mean and one another. The average deviation from the mean for all the data included in the VETYEARS is measured by the standard deviation, which is the square root of the variance. The data are grouped around the mean, as indicated by the comparatively low standard deviation number.
Dependent variable (EVIDU):
The average of the distribution of R ever injectable drug users is shown by the central tendency measures. The mean is calculated by dividing the total number of valid and missing EVIDU data by the total number of values. The mean number of people who have ever injected drugs is 1.97 in the table. When values are ordered from smallest to largest, the midway value is called the median. Based on the data, the median indicates never injecting drugs (2.00). The number that appears the most frequently in the data set is the mode.
The mode in this instance is 2, indicating that the majority of respondents said they had never used an injectable medicine. The dispersion measure shows the EVIDU fluctuation. Each number in the data set's variance is a measurement of its separation from the mean. The table's variance value is really low, indicating that the data points are in close proximity to both the mean and one another. The average departure from the mean for all the data included in the EVIDU is measured by the standard deviation, which is the square root of the variance.
The data are grouped around the mean, as indicated by the comparatively low standard deviation number.
The measure that is frequently employed with nominal variables is the mean, according to what I have learnt from this week's readings and classes. Since VETYEARS and EVIDU have nominal levels of measurement, I believe the mode to be the most accurate way to measure both of these variables. The majority of respondents have not served in the military, and the majority of people have never injected drugs; this is the mode, which summarizes the data for the variables in the frequency table.
References
Neave, H. R. (2022). Statistics tables: For mathematicians, engineers, economists and the behavioural and management sciences. Routledge.
Gunst, M. D., Klaassen, C., & Vaart, A. W. (2023). State of the art in probability and statistics: Festschrift for Willem R. Van Zwet. IMS.
Barnett, V. (2021). Environmental statistics: Methods and applications. John Wiley & Sons.
