1. Happiness Index Survey
Group B: Colin, Andrew, Jae Woo, Matus

2. Life Satisfaction for SU Students (Class)

3. Life Satisfaction UW Data Science Students

4. Life Satisfaction SU Students (not from class)

5. Life Satisfaction (Ages 50-54)

6. Patterns Relative consistency between UW and SU
Male-to-Female, however, shows that male students tend towards slightly more life satisfaction - something consistent with the latest research
The older sample (50-54 year olds) show a more even distribution rather then clumps, with less obvious spikes and more outliers

7. By-the-book Theories and Explanations
According to the U-curve theory, “happiness” and satisfaction levels should be noticeably higher for the older segment. The outliers indeed fit this prediction, having higher extremes then the student data and a marginally higher mean
The gender distinctions slightly contradicts previous studies that females tend to be marginally more satisfied with life, according to the “U-bend in Life” Economist article, which also states that women are “more prone to depression”

8. Personal Theories and Explanations:
Age correlations with satisfaction levels - in addition to the U-curve effect, an equal and opposite reaction accounting for the lowered mean
The average female levels of happiness, however, cannot be fully explained by the Economist article which would have predicted more extreme values rather than consistency
Part of this may be residuals from happiness levels before the so-called “shift”
According to the U-curve, the elderly start being less self-conscious, less stressed about the future, and more willing to “live in the moment” - all of which boosts happiness. I propose an opposite effect where for certain individuals, youthful hopes that have gone unfulfilled and a personally observed negative or stagnant trend leads to a net DECREASE of happiness. This doesn’t necessarily oppose the U-curve, as it is individualized, and both effects taken in concert would explain the data stream and resulting graph where instead of a neat clump we have an almost even distribution with a considerable group of outliers both far below and far above what the student graphs showed.
Female happiness used to be higher than male happiness until about the 60s, when we see what various articles call the “shift” or the “reversal.” Part of the female consistency in the graphs might be residual effects, where they don’t hit as great a low (because their outliers used to be higher than male outliers) but the decreasing happiness rates lower the upper outliers from the final quartile and force a sort of consistency of results.

9. Works Cited
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