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I think most women (who don't have naturally high metabs or have ruined them through dieting since puberty) extreme diet to snag a man. Once the man is snagged, and they have returned to normal eating, BOOM! POW! YIKES! Their true non-svelte self is revealed.
It's not just married people who are fat, practically everyone these days is fat. It boggles my mind. And everyone (without exception) that I know who has had the lapband always gains te weight back. They lose weight the first 1.5 years, then stretch out their stomachs again and then return to their old ways.
Self-discipline is not taught or learned these days. There's no excuse for anyone to be fat. To be thin after 40 you have to work HARD and have self-discipline. If that means getting up at 4:00 am to run 10 miles before work, you do it. I do and weigh the same as I did when I married 21 years ago. Ditto with my husband. Staying thin means constant vigilence and people are too damn lazy to bother with that.
Some men (like my ex) feel very uncomfortable indeed when their baby-weight wife starts to look HOT again. They will do many things to sabotage your efforts, like surprise boxes of chocolates, buying fattening foods, taking you to tempting restaurants.
God... I do NOT get this. I have known women with husbands like this. What is their problem? Why wouldnt any man (or woman) want their partner to look as good as they possibly can? What man would prefer a fat wife over a hot one? What's up with that!??
Once again, this is not a discussion of "DO" people gain weight after they are married. It's a question of "why." And you still have yet to offer one shred of intelligent discussion on "why." Furthermore you buy whole-heartedly into the stats without concerning yourself over reality. This is a simplistic approach.
If stats truly mattered:
-Republicans would NEVER win an election, as Democrats account for 41% of registered voters, while Republicans only 29%.
-The New England Patriots would have won both Super Bowl XLII and XLVI, as they were statistically superior teams than the New York Giants by a long shot.
-The U.S. should never have won its independence from Britain, as it was numerically, tactically, and operationally (feeders for statistics) a superior force.
That's a start. I suppose I could go on. Reality is chalked full of statistical-defying examples. Stats can be a metric, but they rarely (if ever) tell the whole story. You like stats so much. Without the aid of google, can you even tell the class what an R^2 is?
God... I do NOT get this. I have known women with husbands like this. What is their problem? Why wouldnt any man (or woman) want their partner to look as good as they possibly can? What man would prefer a fat wife over a hot one? What's up with that!??
Beauty is subjective. Preferences vary from person to person. And since we all get older and uglier anyway, physical attraction is only temporary.
Once again, this is not a discussion of "DO" people gain weight after they are married. It's a question of "why." And you still have yet to offer one shred of intelligent discussion on "why." Furthermore you buy whole-heartedly into the stats without concerning yourself over reality. This is a simplistic approach.
If stats truly mattered:
-Republicans would NEVER win an election, as Democrats account for 41% of registered voters, while Republicans only 29%.
-The New England Patriots would have won both Super Bowl XLII and XLVI, as they were statistically superior teams than the New York Giants by a long shot.
-The U.S. should never have won its independence from Britain, as it was numerically, tactically, and operationally (feeders for statistics) a superior force.
That's a start. I suppose I could go on. Reality is chalked full of statistical-defying examples. Stats can be a metric, but they rarely (if ever) tell the whole story. You like stats so much. Without the aid of google, can you even tell the class what an R^2 is?
Those examples don't defy statistics. The concept of variation explains it all well. The patriots had like a 70% chance of winning those superbowls. But 1 game has a very high variance. Your point would be valid if they faced the Giants 1 million times and somehow lost the majority of them. In that case, that defy stats.
btw, yes I'm well versed in statistical concepts like R^2 though I feel like these days people make too much of a big deal of small correlations.
I wouldn't be quick to blame marriage for weight gain. Often times people just get caught up with life's demands. You each grind out a 40+ hour work week, commuting, maybe raising children and tending to their needs, doing what needs to be done around the home and before you know it you have less energy or desire for daily exercise. As you age your metabolism slows down as well, so if you are 35 and still eating as you did when you were 22, you'll naturally start to gain weight.
Those examples don't defy statistics. The concept of variation explains it all well. The patriots had like a 70% chance of winning those superbowls. But 1 game has a very high variance. Your point would be valid if they faced the Giants 1 million times and somehow lost the majority of them. In that case, that defy stats.
btw, yes I'm well versed in statistical concepts like R^2 though I feel like these days people make too much of a big deal of small correlations.
If you are familiar with R^2 then you are aware that any given model can only explain so much of a certain given condition. You can always increase the R^2 by adding another independent variable (also known as an "explanatory variable"). For example, let's say that the dependent variable is "weight gain." Our model may be:
Weight gain = Age, Gender, Have Kids, Employment, Distance to Place of Work
Forgive the syntax (or lack thereof). This model would attempt to explain how these explanatory variables influence weight gain. My question to you, (and I've asked now several times) is to discuss the explanatory variables. Rather than to simply say "I'll never get married because married people gain weight" you could actually engage in an intelligent discussion on what some of the causes may be. This in turn could help you and others in the forum by influencing lifestyle decisions and planning ahead so that you can avoid the common mistakes that others make.
It's easy to just look at the stats and come to a conclusion that some researcher has led you to. This requires no critical thought whatsoever. It's another thing entirely to explore what's behind the numbers. You do not seem to have the interest in doing this. Or maybe you just don't have the ability.
If you are familiar with R^2 then you are aware that any given model can only explain so much of a certain given condition. You can always increase the R^2 by adding another independent variable (also known as an "explanatory variable"). For example, let's say that the dependent variable is "weight gain." Our model may be:
Weight gain = Age, Gender, Have Kids, Employment, Distance to Place of Work
Forgive the syntax (or lack thereof). This model would attempt to explain how these explanatory variables influence weight gain. My question to you, (and I've asked now several times) is to discuss the explanatory variables. Rather than to simply say "I'll never get married because married people gain weight" you could actually engage in an intelligent discussion on what some of the causes may be. This in turn could help you and others in the forum by influencing lifestyle decisions and planning ahead so that you can avoid the common mistakes that others make.
It's easy to just look at the stats and come to a conclusion that some researcher has led you to. This requires no critical thought whatsoever. It's another thing entirely to explore what's behind the numbers. You do not seem to have the interest in doing this. Or maybe you just don't have the ability.
It's not my fault that researchers these days don't adjust for every variable, but the study I linked did compare married to single people which is what matters. Married people get fatter than singles.
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