Judakel

@Archaen said:

@Judakel said:

@Archaen said:

@Judakel :

You're doing it wrong.

@People who can read: Enjoy the document.

I sincerely believe that your understanding of this document goes about as far as the introduction. That you read it, due to your poor critical thinking skills missed the words "may", "almost entirely", and the very weak "should not", due to your lack of knowledge on the subject of statistics went no further, and then decided to call it a day. Even the authors of this report agree that, when adjusting for compensable factors, a wage gap remains. If a gap persists after adjusting for all compensable factors, then it must be due to some form of discrimination. They just don't think it is large enough to be concerned about ("should not"), a normative analysis. You can't even tell positive analysis from normative analysis in that introduction.

This is embarrassing for you, but at least you've been outed as the wannabe you always were.

Lol. That is not what the document says. It specifically says later that it does not seem to be from discrimination. You really project yourself into everything, don't you?

Edit: I'm editing this now to let you know that I am closing this tab now. If you can't read a simple PDF correctly I can't help you any further. I fear I've wasted too much time as it is. EnduranceFun was right. I thought I'd give a try.

Having read the entire document before, I can tell that it does not say anything of the sort. More importantly, the math shows it must be discrimination, for when all other factors are adjusted, a gap still persists. The confounding variable is discrimination, pal. You should do the work yourself, if you can.

Please, just be intellectually honest for your own sake.

@Archaen said:

@Judakel :

You're doing it wrong.

@People who can read: Enjoy the document.

I sincerely believe that your understanding of this document goes about as far as the introduction. That you read it, due to your poor critical thinking skills missed the words "may", "almost entirely", and the very weak "should not", due to your lack of knowledge on the subject of statistics went no further, and then decided to call it a day. Even the authors of this report agree that, when adjusting for compensable factors, a wage gap remains. If a gap persists after adjusting for all compensable factors, then it must be due to some form of discrimination. They just don't think it is large enough to be concerned about ("should not"), a normative analysis. You can't even tell positive analysis from normative analysis in that introduction.

This is embarrassing for you, but at least you've been outed as the wannabe you always were.

@Archaen said:

@Judakel said:

@Archaen said:

@Judakel: Lol. Reading comprehension for the FAIL.

P.S. (God, I can't believe someone got me to actually say that)

Where is the reading comprehension "fail"?

I think you essentially understand that you can't do the work that is being asked of you despite your bold declarations that there is no discrimination and time (along with other compensable factors) is the reason why there is wage gap.

Since I added it in an edit, here is the end of the introduction, which you clearly failed to either read or understand:

"Although additional research in this area is clearly needed, this study leads to the unambiguous conclusion that the differences in the compensation of men and women are the result of a multitude of factors and that the raw wage gap should not be used as the basis to justify corrective action. Indeed, there may be nothing to correct. The differences in raw wages may be almost entirely the result of the individual choices being made by both male and female workers."

You should read my previous post, understand it, and then show your work.

@Archaen said:

@Judakel: Lol. Reading comprehension for the FAIL.

P.S. (God, I can't believe someone got me to actually say that). I'm done here. You, sir, cannot manage to accurately read the introduction of the report.

For those that don't want to read a document from a government think tank:

"Although additional research in this area is clearly needed, this study leads to the unambiguous conclusion that the differences in the compensation of men and women are the result of a multitude of factors and that the raw wage gap should not be used as the basis to justify corrective action. Indeed, there may be nothing to correct. The differences in raw wages may be almost entirely the result of the individual choices being made by both male and female workers."

Indeed. I do not have a problem with this statement. I think you're not understanding me. We both agree that the "choice" to work differing amounts of hours clearly contributes to the wage gap. However, it is when we adjust for these "choices" that we see even without these "choices", women will still be paid less than men. Do not ignore "almost entirely" in that statement.

It seems to me the only person who has poor reading comprehension here is you. That, and you apparently stink at stats.

@Archaen said:

@Judakel: Lol. Reading comprehension for the FAIL.

P.S. (God, I can't believe someone got me to actually say that)

Where is the reading comprehension "fail"?

I think you essentially understand that you can't do the work that is being asked of you despite your bold declarations that there is no discrimination and time (along with other compensable factors) is the reason why there is wage gap.

@Archaen said:

@Judakel said:

@Archaen said:

@Judakel said:

@Archaen said:

@Judakel: @Judakel said:

@Archaen said:

They did not do what you think they did. Is that simple enough for you? They don't even say ANYWHERE that they did what you say they did. Everyone else that have done what you think these people have have produced significantly different numbers. Go ahead and run the statistics yourself. Hopefully you'll manage to get the right result, unlike these jokers.

"To compare male and female pay on a level playing field, we found the median pay for all men in a given job, as well as breakdowns of important compensable factors such as years of experience, location, education level, etc. Then, using PayScale's proprietary MarketMatch™ Algorithm, we determined what the female median pay would be using the exact same blend of compensable factors as our control male group."

Please highlight for me in that paragraph where it says they considered hours worked per day or per week. Just highlight it real quick.

"To compare male and female pay on a level playing field, we found the median pay for all men in a given job, as well as breakdowns of important compensable factors such as years of experience, location, education level, etc. Then, using PayScale's proprietary MarketMatch™ Algorithm, we determined what the female median pay would be using the exact same blend of compensable factors as our control male group."

In other words, all factors which affected salary were exactly the same.

Bummer. Because they're not. Nice try, though. If you're good at statistics like you say you are just go ahead and do the work yourself and you'll see that these guys messed up. Not a good source.

I've done the work myself prior to this discussion. They did not mess up.

If you have a different result, please show us your work.

Enjoy the U.S. Department of Labor and Statistics report on the issue, you know, the one everyone is basing their work off of. http://www.consad.com/content/reports/Gender%20Wage%20Gap%20Final%20Report.pdf

Go ahead and tell me they messed up and then we get to throw out every article you or I have posted. lol.

You seem to be rather obtuse. This is essentially the raw data being examined, without being adjusted for compensable factors such as time worked. This data might show that time worked is a factor. However, once this time is adjusted and time worked is no longer a factor, as with the link I posted and my own calculations, we find that a gap persists. You claim that no gap should persist once time is adjusted to be equal. Please show your work.

@Archaen said:

@Judakel said:

@Archaen said:

@Judakel: @Judakel said:

@Archaen said:

They did not do what you think they did. Is that simple enough for you? They don't even say ANYWHERE that they did what you say they did. Everyone else that have done what you think these people have have produced significantly different numbers. Go ahead and run the statistics yourself. Hopefully you'll manage to get the right result, unlike these jokers.

"To compare male and female pay on a level playing field, we found the median pay for all men in a given job, as well as breakdowns of important compensable factors such as years of experience, location, education level, etc. Then, using PayScale's proprietary MarketMatch™ Algorithm, we determined what the female median pay would be using the exact same blend of compensable factors as our control male group."

Please highlight for me in that paragraph where it says they considered hours worked per day or per week. Just highlight it real quick.

"To compare male and female pay on a level playing field, we found the median pay for all men in a given job, as well as breakdowns of important compensable factors such as years of experience, location, education level, etc. Then, using PayScale's proprietary MarketMatch™ Algorithm, we determined what the female median pay would be using the exact same blend of compensable factors as our control male group."

In other words, all factors which affected salary were exactly the same.

Bummer. Because they're not. Nice try, though. If you're good at statistics like you say you are just go ahead and do the work yourself and you'll see that these guys messed up. Not a good source.

I've done the work myself prior to this discussion. They did not mess up.

If you have a different result, please show us your work.

@Archaen said:

@Judakel: @Judakel said:

@Archaen said:

They did not do what you think they did. Is that simple enough for you? They don't even say ANYWHERE that they did what you say they did. Everyone else that have done what you think these people have have produced significantly different numbers. Go ahead and run the statistics yourself. Hopefully you'll manage to get the right result, unlike these jokers.

"To compare male and female pay on a level playing field, we found the median pay for all men in a given job, as well as breakdowns of important compensable factors such as years of experience, location, education level, etc. Then, using PayScale's proprietary MarketMatch™ Algorithm, we determined what the female median pay would be using the exact same blend of compensable factors as our control male group."

Please highlight for me in that paragraph where it says they considered hours worked per day or per week. Just highlight it real quick.

"To compare male and female pay on a level playing field, we found the median pay for all men in a given job, as well as breakdowns of important compensable factors such as years of experience, location, education level, etc. Then, using PayScale's proprietary MarketMatch™ Algorithm, we determined what the female median pay would be using the exact same blend of compensable factors as our control male group."

In other words, all factors that affected salary were exactly the same.

@Archaen said:

@Judakel said:

@Archaen said:

@Judakel said:

@Archaen said:

Wow. I apologize everyone for wasting my time trying to enlighten this person on the facts of income and sex. I hope someone else has found my explanations and the articles I've posted enlightening. This one is a lost cause who wants everyone else in society to pay women for the hours, weeks, months and years that they decide of their own free will not to work. Good luck, you bright, shining star.

You didn't post any facts on income and sex. You posted opinions backed by data that, when adjusted in order to even out the hours, still showed an income disparity.

Not. True. The articles I posted are adjusting the numbers included in your link for the problems inherent to them, which, among many, is that they are using yearly earnings per person ("median pay") for "full time work", which does not take into account, in any way, the fact that men work several more hours per week than women (8.14 hours per day for men and 7.75 hours per day for women). Just look at their methodology:

"Methodology

Difference in Annual Pay: To compare male and female pay on a level playing field, we found the median pay for all men in a given job, as well as breakdowns of important compensable factors such as years of experience, location, education level, etc. Then, using PayScale's proprietary MarketMatch™ Algorithm, we determined what the female median pay would be using the exact same blend of compensable factors as our control male group.

What we created was an apples-to-apples comparison of what men and women make, all other factors held equal, according to actual market data. For example, the male software developer median, annual salary is $65,700, which is 4 percent more than the median female value of $63,300."

There is is again: "Median Pay". Anyone that does a comparison of "Median Pay" is ignoring critical data and their work is inherently incorrect. You are operating on a mathematical fallacy. They say they're showing like for like, but are in fact not doing so, and it's plain to see if you actually look at the numbers. Their numbers also do not take into account many other factors which the 3 articles I linked all cover in detail. There's nothing worse than someone who thinks they know statistics but actually don't. They're impossible to have a discussion with. Please be more careful in the future with whom you believe to be an authority. These people are clearly not.

I have a PhD in Physics from UC Berkeley. I know statistics, son. Not only was it required to obtain my degree, but it is used extensively in my research.

Let me explain something to you: Median is more useful when measuring salaries because the data is not evenly distributed by default. By utilizing the median, you avoid the results being skewed by outliers.

What their mathematical model did was adjust the time spent working to equal amounts for all individuals, adjust the salary accordingly, and then look at results side-by-side. In other words, they got rid of the differences which you utilized to argue that women do not get paid the same because they do not put in the same amount of work. In doing so they revealed that a gap persists even when one controls for these factors. They destroyed your point.

Do you understand this?

They did not do what you think they did. Is that simple enough for you? They don't even say ANYWHERE that they did what you say they did. Everyone else that have done what you think these people have have produced significantly different numbers. Go ahead and run the statistics yourself. Hopefully you'll manage to get the right result, unlike these jokers.

"To compare male and female pay on a level playing field, we found the median pay for all men in a given job, as well as breakdowns of important compensable factors such as years of experience, location, education level, etc. Then, using PayScale's proprietary MarketMatch™ Algorithm, we determined what the female median pay would be using the exact same blend of compensable factors as our control male group."

@Archaen said:

@Judakel said:

@Archaen said:

Wow. I apologize everyone for wasting my time trying to enlighten this person on the facts of income and sex. I hope someone else has found my explanations and the articles I've posted enlightening. This one is a lost cause who wants everyone else in society to pay women for the hours, weeks, months and years that they decide of their own free will not to work. Good luck, you bright, shining star.

You didn't post any facts on income and sex. You posted opinions backed by data that, when adjusted in order to even out the hours, still showed an income disparity.

Not. True. The articles I posted are adjusting the numbers included in your link for the problems inherent to them, which, among many, is that they are using yearly earnings per person ("median pay") for "full time work", which does not take into account, in any way, the fact that men work several more hours per week than women (8.14 hours per day for men and 7.75 hours per day for women). Just look at their methodology:

"Methodology

Difference in Annual Pay: To compare male and female pay on a level playing field, we found the median pay for all men in a given job, as well as breakdowns of important compensable factors such as years of experience, location, education level, etc. Then, using PayScale's proprietary MarketMatch™ Algorithm, we determined what the female median pay would be using the exact same blend of compensable factors as our control male group.

What we created was an apples-to-apples comparison of what men and women make, all other factors held equal, according to actual market data. For example, the male software developer median, annual salary is $65,700, which is 4 percent more than the median female value of $63,300."

There is is again: "Median Pay". Anyone that does a comparison of "Median Pay" is ignoring critical data and their work is inherently incorrect. You are operating on a mathematical fallacy. They say they're showing like for like, but are in fact not doing so, and it's plain to see if you actually look at the numbers. Their numbers also do not take into account many other factors which the 3 articles I linked all cover in detail. There's nothing worse than someone who thinks they know statistics but actually don't. They're impossible to have a discussion with. Please be more careful in the future with whom you believe to be an authority. These people are clearly not.

I have a PhD in Physics from UC Berkeley. I know statistics, son. Not only was it required to obtain my degree, but it is used extensively in my research.

Let me explain something to you: Median is more useful when measuring salaries because the data is not evenly distributed by default. By utilizing the median, you avoid the results being skewed by outliers.

What their mathematical model did was adjust the time spent working to equal amounts for all individuals, adjust the salary accordingly, and then look at results side-by-side. In other words, they got rid of the differences which you utilized to argue that women do not get paid the same because they do not put in the same amount of work. In doing so they revealed that a gap persists even when one controls for these factors. They destroyed your point.

Do you understand this?