Crossposted from https://www.reddit.com/r/dataisbeautiful/comments/8rj2k9/linear_regression_of_weight_loss_with_increasing/
High-resolution PNG of chart
Google Sheets with raw data and chart
This past January, I decided to start losing some weight. I bought a scale for my food, and a scale for myself. I tracked my body weight several times a day to get a good sense of how much it fluctuated per day, then looked at longer-term trends to monitor my progress. A common complaint in forums such as /r/loseit is that the number on the scale can jump around quite a bit, and when it increases it can be a discouraging sign. This often leads to less frequent weigh-ins, resulting in lower quality of data. I wanted to show how considering longer-term trends not only gives a more accurate representation of true weight loss, but confronts the irrational fear of seeing the number on the scale.
The raw data is from 878 weigh-ins taken between January 10, 2018 and June 16, 2018. It has been summarized by taking the minimum observed weight for each calendar day. A least-squares estimation regression model was then calculated for each day with an ever-increasing trailing window, starting at 7 days and ending at 42 days. The slope of each of the 36 windows is then plotted on the chart. Line thickness increases as window size increases, giving emphasis to longer-term trends. The rainbow colour scheme was originally taken from the default Google Sheets palette. Since then, I have discovered how to programmatically assign colours via the Charts API, but decided to keep the colour progression. All other chart features (legends, axes, titles, etc.) were deliberately removed to maintain a minimalist look and to emphasize the smoother nature of a longer trend window. Final preparations were done in Photoshop.
It is interesting to see when so-called "treat days" happened, where large upward spikes are shown in the short-term trendlines. It is also interesting (and encouraging to those losing weight) to see that every upward swing is accompanied shortly thereafter with an equal or greater downward swing. This shows that although body weight can fluctuate wildly over the course of even a day or two, that gain is almost completely attributed to "poop weight": food and drink we have ingested but not yet eliminated. Once the subsequent bowel movements have occurred (typically in 1-4 days), body weight returns to normal. This proves that occasional treat days are not detrimental to weight loss goals, and in fact may be recommended as stress relief from strict adherence to dietary regimens.
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