Recent comments in /f/dataisbeautiful

ketzu OP t1_jbxabcr wrote

Based on the article: The relationship between income and well-being is well known to be log-linear, i.e., well-being increases based on the log of income, but the spread is fairly wide. One goal of the article seemed to be to investigate the popular "you won't be any happier after making $75k/year" and found that it is not the case, besides a small, unhappy, group.

My personal interpretation is:

More money => more happy, but not as much as one might think. Many are happy while poor and many are unhappy with high income. But that might be for many different reasons: Your level of satisfactions could just move up your baseline for when to feel better: Before, being able to afford a nice steak made you happy, now you can eat steak every day and it just doesn't cut it anymore.

The improvements are "very strong" in the low end (here you can see it better I believe), but not as much later on. If you are unhappy at $75k, I think it is unlikely that a higher income will increase your well-being in the long run (I am pretty sure most people are happy moving up on the income ladder at least short term).

But people are different, maybe for an individual that's exactly what is missing in their lives.

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ketzu OP t1_jbx8vq8 wrote

In the publication it is measured via smartphone app at random times in the day (with respect to the participants sleeping schedules).

> After providing informed consent, participants completed an intake survey, which included demographic questions as well as two measures of life satisfaction, as detailed below. The participants were next asked to indicate the times at which they typically woke up and went to sleep, and how many times during the day they wished to report on their experiences (default = 3). A computer algorithm then divided each participant’s day into a number of intervals equal to the number of desired reports, and a random time was chosen within each interval. New random times were generated each day, and the times were independently randomized for each participant. At each of these times, the participants were signaled via a notification on their smartphone, asking them to respond to a variety of questions about their experiences at the moment just before the signal. The experienced well-being question was asked in every survey. Other questions unrelated to the present investigation were also asked. The participants received notifications requesting a report until they chose to discontinue participation. If 50 samples had been collected, reporting stopped for 6 mo or until the participant requested that it be restarted.

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ketzu OP t1_jbx7d0a wrote

Datasource is a scientific article:

I am not affiliated with the article or authors at all, I just used their published data.

The plot was made using seaborns violin plot and some surrounding stuff (file link).

violin = sb.violinplot(data, x='income', y='wellbeing', scale='count', inner='quartile', width=1.3)
violin.set(xlabel="Income Bracket", ylabel="Wellbeing")
violin.set_xticks(range(15), labels)
violin.set_title("Violin Plot of Wellbeing Distribution, Including Q1, Median, Q3 Highlights")

I also made another plot using pyplot to generate statistics accross the income brackets (p10, q1, median, q3 and p90). I like hat one more, but it is even less pretty.

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