Quantifying Happiness - bmc.DSCI.B210.001.F26
Section outline
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Version 1.0 posted on August, 31, 2026.
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Updated 2/19/24 (after snow day)
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Guide from last time course was offered. Will be updated and dates changed.
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Due: Saturday, May 2, 2026, 2:20 PM
Post by class on Thursday, 9/3. We will discuss these posts in class on 9/8
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This link is private and cannot be shared with anyone outside of class
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Come to class ready to discuss the film. What struck you? What does it teach us about happiness? What parts were particularly interesting or moving? What character(s) did you particularly like? What is missing? Any ways the film could have been improved?
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Due: Thursday, September 17, 2026, 2:39 PM
LinkedIn Learning "Modules" that should be completed before class today
1. Pivot Tables (includes hints about how to clean up a “messy” database”)
· When complete, upload ascreenshot (see example on syllabus) of completed modules to this assignment portal
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· PAY PARTICULAR ATTENTION TO DATA TYPES (GREEN BOX) starting on page 46
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Due: Tuesday, September 22, 2026, 2:39 PM
When complete, upload ascreenshot of completed modules to this assignment portal
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Nilsson, A.H., Eichstaedt, J. C., Lomas, T. & Kjell, O. (2024) The Cantril Ladder elicits thoughts about power and wealth. Scientific Reports 14, 2642 (2024).
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Due: Sunday, May 10, 2026, 2:15 PM
Look at LIWC (LIWC described in article) https://www.liwc.app/demo. Try it with some text you “harvest” from a social media post.
Then post on this Moodle Forum below the text you scraped and the LIWC report (screenshots are fine) with some comments highlighting what you noticed
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Be prepared to discuss (from House et al):
· Essential Methods & Samples
· Figure 1 and 2: What is the “Headline” for these figures?
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Some time before class, talk to a stranger or someone you do not really know that well (e.g., worker in dining hall or post office). Jot down a few notes about what it was like. For example:
What did you worry about? How did it go?
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Enjoy Break!!
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Link to Online version of article: https://www.sciencedirect.com/science/article/pii/S235282732200310X
Come prepared to talk about:
• Overall impressions
• Methods (strengths & weaknesses)
• Key Findings (what is most important takeaway?)
• Discussion of implications of findings (are these findings important? what is particularly worrisome here?
• Links between Social Isolation and Loneliness
• Possible ways to address social isolation
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Remaining part (264-288) is optional
The assignment for Data Visualization Lab #4 will involve a SCATTERPLOT. Please review the Scatterplot module (less than 8 minutes long) in the LinkedIn Learning course on Excel. For those still mastering Excel, it will be useful to practice with the sample data along with the video.
A FEW THINGS TO NOTE:
- be sure to be prepared to add a trendline (best fitting line) and R squared value (and note how you can reformat or manipulate both) to your scatterplot
- In the case of one x variable (one predictor) the value of R-squared is equal to lthe value of ittle r-squared. Little r-squared tells you how much variation the x and y variable share.
- the narrator in the Excel video characterizes a correlation ("r" or the sqrt of r-squared) of .5 as not being strong. We have talked in class about the common standards in social science research (r=.5=large; r=.3=medium; r=.1=small). In your write-up, I would like you to use the common social science standard.
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