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2-1 Discussion: Controls, Variables, Confounding Results Hello all! PART ONE: I chose to evaluate Jackie’s recycling investigation of her neighborhood for this discussion post part one. 1. Model: recycling 2. Independent: age and political party because that is how she is categorizing her groups as to a reason for why they recycle or not. Dependent: if they put their recycling out/recycling because that is what she is “measuring”. 3. Treatment groups: her neighbors are her treatment group because that is who she is analyzing whether they recycle or not. 4. Controls: same survey, asking every neighbor in her neighborhood, making sure everyone can recycle. 5. Extraneous factors: does it cost more to have a recycling bin? Does your city make you have a recycling bin? Is it an all in one recycle bin or is there multiple separate bins that has to be categorized? Recycling is not always an “easy” task that becomes habitual, some places it takes a lot of effort to be able to recycle which makes it less convenient and unappealing for people to do. PART TWO: The idea or ability to control for confounding variables can vary depending on what kind of study or research is being conducted. Controlling confounding variables is important to research however whether your study involves humans, animals, plants, etc. In a controlled experiment researchers have a better chance of controlling confounding variables. There are additional aspects that can also help to control such as randomization which I talked about in our last discussion post regarding bias. When it comes to a human study however, the extenuating variables are really endless. The article regarding smoking and risk factors to children really highlights the numerous variables that can come from a research study involving humans. The study of human behavior is severely hampered by logistical problems, ethical and legal constraints, and funding shortfalls. However, the biggest difficulty of conducting social and behavioral research is the extraordinary complexity of the study phenomena in humans (Sanbonmatsu, 2021). In the reading for this week, it was stated that “children of parents who smoke are at a higher risk for lifestyle diseases” (Burke, 1998). This study seems to present bias to persuade readers to think one way regarding the habitual act of smoking. The age ranges also lacked data in the article as well as some discrepancies with medical/preexisting conditions and the information gathered. Buncher, C. ScD, Morrison, J. PhD. (1998 August). Those confounding variables!. The Journal of Pediatrics, 133 (2), 174-175. Burke, V., Gracey, M. P., Milligan, R. A. K., Thompson, C., Taggart, A. C., & Beilin, L. J. (1998, August 1). Parental smoking and risk factors for cardiovascular disease in 10- to 12-year- old children. Journal of Pediatrics , 133 (2), 206.

Sanbonmatsu, D. M., Cooley, E. H., & Butner, J. E. (2021). The Impact of Complexity on Methods and Findings in Psychological Science. Frontiers in psychology , 11 , 580111. https://doi.org/10.3389/fpsyg.2020.580111

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