Final

2024/4/25 20:37 Final Project

https://utah.instructure.com/courses/930100/assignments/13787480 1/12

Final Project

Due Wednesday by 11:59pm Points 50 Submitting a text entry box or a file upload

Start Assignment

The goal of this final presentation is to show off your newfound understanding of statistics by explaining some real-world statistical analysis as if you’re explaining it to someone with no statistics background. You will select some statistical analysis from a reputable source and proceed to explain it in a 5-7 minute prerecorded presentation.

The statistics you choose to explain:

1. Must be from a reputable source, such as a peer-reviewed article, a government report, or original research from a well know journalism outlet. Note that if you find a news article about a new report or academic study, you cannot use the news article, you must use the original source they are reporting on. If you have any questions about if a source is acceptable, feel free to email me and ask.

2. Needs to include some inferential statistics. If the study you used includes nothing that you recognize as inferential statistics, you should find another source. If your source only uses descriptive statistics that doesn’t mean its bad in general, just not a good choice for this assignment.

3. Should be mostly things you understand. There will almost always be types of analysis that you are unfamiliar with, but it will usually be some variation of something we have done already. So if you run into a “nested model” or “fixed effects” you probably won’t understand them fully, but you can look at them and see they are some form of regression analysis. You can explain the parts that we covered in this course, and simply explain that you have not learned what makes this different from what you know. It is fine to say you don’t know. But, if most of the analysis is things you don’t understand then you’re going to struggle.

4. Should be something you’re interested in. It’ll make the whole process more interesting and easier for you. But if you don’t want to find the time to find something interesting and just want to find the first thing you can then don’t worry, just do what you want.

Your presentation:

1. Must include both audio and visual components. Whether that’s a video of your voice over a slideshow or a video of you actually giving the presentation, it really doesn’t matter. Your face doesn’t have to be in the video at all if you don’t want it to be. Also if you’re good enough at text-to-speech then I suppose your voice doesn’t have to be in it either, but just know that the lack of expressiveness in a TTS voice will make your presentation far less enjoyable.

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2. Must explain 2-4 statistical concepts that we have covered in this class. If you only cover two, any slight errors or omissions in your presentation will affect your grade more. At least one topic covered must be from module 6 or afterwards, so you cant get away with explaining mean, median, and mode.

3. Should be between 5 and 7 minutes long. If you know what you’re talking about, 5 minutes is plenty to explain a few statistical concepts. If it is taking you longer than 7 minutes it might indicate that you don’t understand the concepts as well as you think. If you can get everything required done in under 5 minutes, go for it, but you better really have it down.

4. Should contain an introduction to the analysis you’re covering (what did it do in general?), an explanation of what was done (explain what they did, and the statistical concepts they used), and a conclusion (what was the takeaway from the article, and why is it important to be able to understand the statistics?)

2024/4/25 20:37 Final Project

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My "guide" to finding sources for this assignment. Additional sources that I think will be useful are below.

2024/4/25 20:37 Final Project

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finding sources 

  0:00 / 20:16 1x1x

(Youtube link to finding sources) (https://youtu.be/mfRLwIIgKzo)

A guide to what I think is the easiest way to record your videos, and some more discussion of what I expect your presentation will look like.

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How to upload 

  0:00 / 17:08 1x1x

(Youtube link to How to Upload) (https://youtu.be/MiQnCQhlGvc)

Update 12/5/23

I have been getting a number of emails from students asking some clarifying questions about the final project, and also asking me if specific sources look good to use for the project. So I will answer some questions for you here and then say some more about sources. I will also put this information in the project assignment page.

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Questions:

Does the source need to be recent? No! if you find a source that meets the requirements of containing some form of inferential statistics, then It doesn't matter when it is from. I was going to suggest that you could even use Svante Arrhenius's 1986 paper On the Influence of Carbonic Acid in the Air Upon the Temperature of the Ground in which he correctly predicts that increased carbon concentrations in the atmosphere would lead to increased global temperatures (That's predicting global warming in 1896, with tons of data) but it actually didn't have anything we would recognize as inferential statistics. largely because it predates most of what we would call inferential statistics. SO it has to be somewhat recent, anything over 100 years old will be tough, over 60-70 years old might be tough too, but any time period is fine.

When you discuss multiple topics can they come from multiple papers or just one? My preference is for you to use just one article as your source for all of the topics. Since you must have a source that covers inferential statistics, I guarantee that it will cover at least 2-3 other topics you could cover. I consider central tendency to be a topic, variability is a topic, validity, reliability, correlation, R , etc. all of those are topics (but there are plenty of others, those are just some examples), and I know your source will have to say something about some of these other topics.

If you have questions about a specific source please let me know, I will be happy to take a quick look and let you if i think it will work, and any suggestions of what I would like to see from it.

A lot of people have told me they are struggling to find a source that works, as they are finding it difficult to find sources that both cover enough and are still understandable. I apologize that I cannot get back into the mindset of someone who is at your stage in their statistics education. I fell like that sounds sarcastic but I do mean it. I have taken stock and gone through the process of trying to find sources while thinking "How do I know to do what I am doing" throughout and I realized how much slower this process would be if I didn't have the experiences I do. For me, I can read a article title and have a pretty decent idea of what type of statistics are involved because I know what statistics would be needed to answer that type of question, and that is not something I have taught to you, nor could I have in one semester. So, I propose some options:

If you find a source that does not contain inferential statistics but does have data that could be used, I will allow you to propose what inferential statistics could have been done. This is a bit risky for you, in my opinion, because finding a paper that does a t-test and explaining it is much easier than finding a paper, creating a question that could be answered, deciding it needs to be answered with a t-test and then explaining a t-test. I still would not require you to complete or even attempt the test, however, if you explained a t-test but the question you described would actually require ANOVA, you would be wrong and would then lose some points, so it is better for you to find someone else’s work and just comment on it. I will try to create a list of sources that I think are going to be easier for you to understand but still meet the requirements. Most of these, at least initially, will be heavily skewed towards environmental sociology, and specifically cross-national comparisons, as I will be pulling from my own experiences. If you have some other topics you’d like me to add to a list I am happy to try to add some. I am going to include a short video of how I recommend you find a source, but that might not be available for a day or so.

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I also am planning to include a video of how to use canvas to record a video entirely in your browser so that you can have a smooth process of uploading your videos.

As always, I am open to suggestions. I'm sorry that you're getting the short end of the stick with this being the first time this project is done this way, so I am always willing to make necessary changes to make things go smoother for unintended frictions caused by the project.

Below is a preliminary list of sources that I think have enough statistics in them but are not at such a high level as to be completely foreign to you.

The papers are split up by topic, but some that would fit in multipole topics may not be where you thing (e.g. papers about gender inequality may be in either gender or inequality.) Along side each citation is a mention of what methodology the paper uses that covers the inferential statistics requirement. In parentheses are specifics about the methodology that we have not learned in this class. So we have covered linear regression, but not Logit regressions, for example. In these cases it is alright for you to say "I do not know what __________ means exactly, but if this was like what we learned in class, this is what it would mean." If I missed anything in any of these articles that you come across and you think we have not covered, it is probably okay to do the same, but feel free to email me for clarification, and I can add it to the list below.

If you're still interested in a topic and cannot find anything let me know, I will try to look for you and add any options I find to the list.

Environmental sociology:

Paper Method

Fitzgerald, Jared B., Juliet B. Schor, and Andrew K. Jorgenson. 2018. “Working Hours and Carbon Dioxide Emissions in the United States, 2007–2013.” Social Forces 96(4):1851–74. doi: 10.1093/sf/soy014

(https://doi.org/10.1093/sf/soy014) .

Regression (fixed effects and random effects)

Jorgenson, Andrew, Juliet Schor, and Xiaorui Huang. 2017. “Income Inequality and Carbon Emissions in the United States: A State-Level Analysis, 1997– 2012.” Ecological Economics 134:40–48. doi: 10.1016/j.ecolecon.2016.12.016 (https://doi.org/10.1016/j.ecolecon.2016.12.016) .

Regression (longitudinal, fixed effects)

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Adua, Lazarus. 2022. “Super Polluters and Carbon Emissions: Spotlighting How Higher-Income and Wealthier Households Disproportionately Despoil Our Atmospheric Commons.” Energy Policy 162:112768. doi: 10.1016/j.enpol.2021.112768 (https://doi.org/10.1016/j.enpol.2021.112768) .

Regression

Adua, Lazarus, Richard York, and Beth-Anne Schuelke-Leech. 2016. “The Human Dimensions of Climate Change: A Micro-Level Assessment of Views from the Ecological Modernization, Political Economy and Human Ecology Perspectives.” Social Science Research 56(C):26–43. doi: 10.1016/j.ssresearch.2015.10.003 (https://doi.org/10.1016/j.ssresearch.2015.10.003) .

Regression

Dietz, Thomas, Eugene A. Rosa, and Richard York. 2007. “Driving the Human Ecological Footprint.” Frontiers in Ecology and the Environment 5(1):13–18. doi: 10/ffvs4x (https://doi.org/10/ffvs4x) .

Regression (STIRPAT – uses lots of logged variables)

Rosa, Eugene A., Richard York, and Thomas Dietz. 2004. “Tracking the Anthropogenic Drivers of Ecological Impacts.” Ambio 33(8):509–12. doi: 10.1579/0044-7447-33.8.509 (https://doi.org/10.1579/0044-7447-33.8.509) .

Regression (STIRPAT – uses lots of logged variables)

York, Richard, Eugene A. Rosa, and Thomas Dietz. 2003. “STIRPAT, IPAT and ImPACT: Analytic Tools for Unpacking the Driving Forces of Environmental Impacts.” Ecological Economics 46(3):351–65. doi: 10.1016/S0921-8009(03)00188-5 (https://doi.org/10.1016/S0921-8009(03)00188-5) .

Regression (STIRPAT – uses lots of logged variables)

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Gender:

Paper Method

Geist, C. 2005. “The Welfare State and the Home: Regime Differences in the Domestic Division of Labour.” European Sociological Review 21(1):23–41. doi: 10/bsnzq6 (https://doi.org/10/bsnzq6) .

Regression (Logit)

Aryal, Jeetendra Prakash, Tek Bahadur Sapkota, Dil Bahadur Rahut, Hom Nath Gartaula, and Clare Stirling. 2022. “Gender and Climate Change Adaptation: A Case of Ethiopian Farmers.” Natural Resources Forum 46(3):263–88. doi: 10.1111/1477- 8947.12259 (https://doi.org/10.1111/1477- 8947.12259) .

t-testing and regression (Probit)

Raparthi, Kiranmayi. 2021. “Assessing the Relationship Between Urban Planning Policies, Gender, and Climate Change Mitigation: Regression Model Evaluation of Indian Cities.” Journal of Urban Planning and Development 147(2):05021007. doi: 10.1061/(ASCE)UP.1943-5444.0000677 (https://doi.org/10.1061/(ASCE)UP.1943- 5444.0000677) .

Regression

Eastin, Joshua. 2018. “Climate Change and Gender Equality in Developing States.” World Development 107:289–305. doi: 10.1016/j.worlddev.2018.02.021 (https://doi.org/10.1016/j.worlddev.2018.02.021) .

Regression (ordered logistic)

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Hook, Jennifer L. 2010. “Gender Inequality in the Welfare State: Sex Segregation in Housework, 1965–2003.” American Journal of Sociology 115(5):1480–1523. doi: 10.1086/651384 (https://doi.org/10.1086/651384) .

Regression (Tobit, multi-level modelling)

Health

Paper Method

Rodriguez, Javier M., John Bound, and Arline T. Geronimus. 2014. “US Infant Mortality and the President’s Party.” International Journal of Epidemiology 43(3):818–26. doi: 10/f58t32 (https://doi.org/10/f58t32) .

Regression (time series)

Reynolds, Megan M., and Veerle Buffel. 2020. “Organized Labor and Depression in Europe: Making Power Explicit in the Political Economy of Health.” Journal of Health and Social Behavior 61(3):342–58. doi: 10/ghmbt7 (https://doi.org/10/ghmbt7) .

Regression (multi-level modelling)

Inequality

Paper Method

Cole, Wade M. 2018. “Poor and Powerless: Economic and Political Inequality in Cross-

Regression (Two stage Least squares)

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National Perspective, 1981–2011.” International Sociology 33(3):357–85. doi: 10/gddvfn (https://doi.org/10/gddvfn) .

Yang, Tiantian, and Howard E. Aldrich. 2014. “Who’s the Boss? Explaining Gender Inequality in Entrepreneurial Teams.” American Sociological Review 79(2):303– 27. doi: 10.1177/0003122414524207 (https://doi.org/10.1177/0003122414524207) .

Regression (Conditional Logistic)

Jacobs, David, and Lindsey Myers. 2014. “Union Strength, Neoliberalism, and Inequality: Contingent Political Analyses of U.S. Income Differences since 1950.” American Sociological Review 79(4):752– 74. doi: 10.1177/0003122414536392 (https://doi.org/10.1177/0003122414536392) .

Criminology:

Paper: Method

Edgemon, Timothy G., and Jody Clay- Warner. 2019. “Inmate Mental Health and the Pains of Imprisonment.” Society and Mental Health 9(1):33–50. doi: 10.1177/2156869318785424 (https://doi.org/10.1177/2156869318785424) .

Regression (uses structural equation modelling and confirmatory factor analysis to determine variables, but results can be interpreted as linear regession)

Domino, Marisa Elena, Alex Gertner, Brigid Grabert, Gary S. Cuddeback, Trenita Childers, and Joseph P.

t-testing, regression (uses a lot of variations of regression)

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Morrissey. 2019. “Do Timely Mental Health Services Reduce Re- Incarceration among Prison Releasees with Severe Mental Illness?” Health Services Research 54(3):592–603. doi: 10.1111/1475-6773.13128 (https://doi.org/10.1111/1475-6773.13128) .

Baćak, Valerio, Lars H. Andersen, and Jason Schnittker. 2019. “The Effect of Timing of Incarceration on Mental Health: Evidence from a Natural Experiment.” Social Forces 98(1):303–28. doi: 10.1093/sf/soy102 (https://doi.org/10.1093/sf/soy102) .

t-test, Regression (regression data located in supplemental tables available here (https://academic-oup- com.ezproxy.lib.utah.edu/sf/article/98/1/303/5145053#supplementary- data) )

Electoral Politics/Voting

Paper Method

Swartz, Teresa Toguchi, Amy Blackstone, Christopher Uggen, and Heather McLaughlin. 2009. “WELFARE AND CITIZENSHIP: The Effects of Government Assistance on Young Adults’ Civic Participation.” The Sociological Quarterly 50(4):633– 65. doi: 10.1111/j.1533-8525.2009.01154.x (https://doi.org/10.1111/j.1533-8525.2009.01154.x) .

Regression (Logistic regressions)

Kupchik, Aaron, and Thomas J. Catlaw. 2015. “Discipline and Participation: The Long-Term Effects of Suspension and School Security on the Political and Civic Engagement of Youth.” Youth & Society 47(1):95–124. doi: 10.1177/0044118X14544675 (https://doi.org/10.1177/0044118X14544675) .

Regression (Logistic regressions)

Gaby, Sarah. 2017. “The Civic Engagement Gap(s): Youth Participation and Inequality From 1976 to 2009.” Youth & Society 49(7):923–46. doi: 10.1177/0044118X16678155 (https://doi.org/10.1177/0044118X16678155) .

Regression (Logistic regressions)

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