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[Seth Roberts]

Here are two new weight tracking graphs. The first is similar to the graphs Rey has been making. The second shows everyone's data "normalized" so that they start at day = 0 and weight = 0. The second one is especially interesting: Although most people are losing weight at a rate between 1 pound/week and 3 pounds/week, there is a substantial subset of people who are not losing at all. It's not a normal distribution of rates of weight loss -- it is a distribution with two peaks, one at 2 pounds/week and the other at about 0 pounds/week.





suggestions for improvement welcome. I am also interested in your ideas about other helpful ways to graph this data.

[Ann H]

Although most people are losing weight at a rate between 1 pound/week and 3 pounds/week, there is a substantial subset of people who are not losing at all. It's not a normal distribution of rates of weight loss -- it is a distribution with two peaks, one at 2 pounds/week and the other at about 0 pounds/week.

That is really interesting. And it mirrors what posts on these forums seem to indicate: easy (if slow) weight loss for many (most?), nothing or irregular ups and downs for some.

Seth, can you break off that subset of folks not on the normal losing trend and analyze them a bit? Are they all people near target weight, all female, all oil users, all ... ?? (The icons are too small for me to be able to pick out who they are.)

Then I'm wondering: for this non-losing subset, would significantly upping the ratio of flavorless calories help? Or changing onto sugar water from oil, perhaps?

Ann H 

[94S10 (a.k.a. Truckman)]

Although most people are losing weight at a rate between 1 pound/week and 3 pounds/week, there is a substantial subset of people who are not losing at all. It's not a normal distribution of rates of weight loss -- it is a distribution with two peaks, one at 2 pounds/week and the other at about 0 pounds/week.

That is really interesting. And it mirrors what posts on these forums seem to indicate: easy (if slow) weight loss for many (most?), nothing or irregular ups and downs for some.

Of course Seth can only track those who have reported their weight loss. I'm guessing that the reason there is more "positive" weight loss data is that its easier to come here and say how easy/great the weight loss has been (even if slow) than to come here and admit that you are not losing.

[Seth Roberts]

Thanks, Ann, for your suggestion. I plan to make graphs that show the effect of various factors, such as sex, age, and initial weight.

[frenata]

More graphs! I love graphs!

[dgrillot2000]

Seth, can you break off that subset of folks not on the normal losing trend and analyze them a bit? Are they all people near target weight, all female, all oil users, all ... ??
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My first thought when I see a bimodal distribution for humans is that the different peaks are gender related.  My guess is that if you break out the males and females into separte distributions you will remove the bimodality.

[Ann H]

My first thought when I see a bimodal distribution for humans is that the different peaks are gender related.  My guess is that if you break out the males and females into separte distributions you will remove the bimodality.

That's a neat thought and worth checking out. Perhaps when you sort by gender it'll realign such that you get fairly "normal" distributions for both genders, but with a heavy end at "not losing" for the females, while a lighter "not losing" end for the males. Worth looking at!

[dgrillot2000]

Seth,

On the first graph I think if you could expand the scale on the vertical axis which should make it more readable.  I could barely find my data in the mix of several others.  Whatever the scale was which you used on the web page www.sethroberts.net seems to discriminate between the individual's data much better.

On the graph with the "normalized" data, I'm not sure why you plotted the average as opposed to plotting regression lines.  (Perhpas averaging was the easiest to do for a first cut.)  Actually, since the rate of weight loss is generally proportial the weight, an exponential regression would perhaps give a better fit of the data.  I'm not sure how difficult this is to do with your software, but in some later excel systems this capability is present.

I'm not sure how far you intend to push the analysis of this data.  Or perhpas your intent is merely for display purposes for others to see.   A statistician could analize this data until the proverbial cows come home.

DG

P.S. This is my 100th post.  I think something special happens at this point.  Maybe I'll turn into a skinny prince rather than a chubby frog. 

[frenata]

P.S. This is my 100th post.  I think something special happens at this point.  Maybe I'll turn into a skinny prince rather than a chubby frog. 

No, the weight stays the same, but you get a bigger member.

Don't mess with me, Hoss. Mine's a hero.

[Rey]

No, the weight stays the same, but you get a bigger member.

Don't mess with me, Hoss. Mine's a hero.

hmmm... there may be some new reasons to post a lot in the forum then ;-) (LOL)

[Seth Roberts]

dgrillot2000, I called the "average" line "average" so that most people could understand what it is -- it is a summary. It is not a mean; the procedure I used is called "lowess", a term which would baffle almost anyone who isn't a statistician. It is an advanced form of regression.

[dgrillot2000]

 I called the "average" line "average" so that most people could understand what it is -- it is a summary. It is not a mean; the procedure I used is called "lowess", a term which would baffle almost anyone who isn't a statistician. It is an advanced form of regression.

~~~~~~~~~~~~~

Thanks, now I understand why there are wiggles in the red line. 

[Gregg]

Are these graphs ever going to be updated?

[Seth Roberts]

yes, they will be updated soon. I've been travelling a lot.