Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
Right....so starting a thread about personally experiencing sexism but won't elaborate? What is the point of the thread?
the point of the thread wasn't about personal experience, but it may have been what inspired the need to post about the topic. from what I know of Kat, you won't receive the answer you seek. Nor should you expect to.
it is a FACT that women make about 70% of the wages men do for doing the same job. if that isn't enough in and of itself, I don't know what is.
if YOU made 7/10 of what a woman made at what you do, for no other reason than your gender, damn right you'd be pissed about it, don't you think?
I hear what you are saying. I just don't get that all these women and proponent males of their voice who say they make less but don't give concrete examples other than statistics and graphs.
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.
I know how to read a graph of statistics. The one posted above does not mean anything to anyone. It is merely numbers and mean as much as the polls that showed Hillary was a shoe in.
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your first point - Are you saying that a female in the USA will make less statistically at say Starbucks?, insert any restaurant name etc.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
1. You missed what I said & what I meant, and that's fine. 2. If you think that Projections (I'll spell this out for you...projections are basically G-U-E-S-S-ES) are the same as Statistics (which are based on F-A-C-T-S), then you are a bit more misguided than you may realize. I have never paid any attention to projections because I know that they are flawed and that their origin basically comes from a guessing game or agenda.
Trump won, I get it. Enjoy the living fuck out of it...seriously. The conversation we are having isn't about Trump...and you don't seem to see that.
Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
Right....so starting a thread about personally experiencing sexism but won't elaborate? What is the point of the thread?
the point of the thread wasn't about personal experience, but it may have been what inspired the need to post about the topic. from what I know of Kat, you won't receive the answer you seek. Nor should you expect to.
it is a FACT that women make about 70% of the wages men do for doing the same job. if that isn't enough in and of itself, I don't know what is.
if YOU made 7/10 of what a woman made at what you do, for no other reason than your gender, damn right you'd be pissed about it, don't you think?
I hear what you are saying. I just don't get that all these women and proponent males of their voice who say they make less but don't give concrete examples other than statistics and graphs.
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.
I know how to read a graph of statistics. The one posted above does not mean anything to anyone. It is merely numbers and mean as much as the polls that showed Hillary was a shoe in.
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your first point - Are you saying that a female in the USA will make less statistically at say Starbucks?, insert any restaurant name etc.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
1. You missed what I said & what I meant, and that's fine. 2. If you think that Projections (I'll spell this out for you...projections are basically G-U-E-S-S-ES) are the same as Statistics (which are based on F-A-C-T-S), then you are a bit more misguided than you may realize. I have never paid any attention to projections because I know that they are flawed and that their origin basically comes from a guessing game or agenda.
Trump won, I get it. Enjoy the living fuck out of it...seriously. The conversation we are having isn't about Trump...and you don't seem to see that.
I'm just using Trump winning as an evidence based fact steeped by opposing projections and statistics. As opposed to anyone providing a clear and concrete example of a female making less than a male in the same job. Anyone?
Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
Right....so starting a thread about personally experiencing sexism but won't elaborate? What is the point of the thread?
the point of the thread wasn't about personal experience, but it may have been what inspired the need to post about the topic. from what I know of Kat, you won't receive the answer you seek. Nor should you expect to.
it is a FACT that women make about 70% of the wages men do for doing the same job. if that isn't enough in and of itself, I don't know what is.
if YOU made 7/10 of what a woman made at what you do, for no other reason than your gender, damn right you'd be pissed about it, don't you think?
I hear what you are saying. I just don't get that all these women and proponent males of their voice who say they make less but don't give concrete examples other than statistics and graphs.
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.
I know how to read a graph of statistics. The one posted above does not mean anything to anyone. It is merely numbers and mean as much as the polls that showed Hillary was a shoe in.
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your first point - Are you saying that a female in the USA will make less statistically at say Starbucks?, insert any restaurant name etc.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
1. You missed what I said & what I meant, and that's fine. 2. If you think that Projections (I'll spell this out for you...projections are basically G-U-E-S-S-ES) are the same as Statistics (which are based on F-A-C-T-S), then you are a bit more misguided than you may realize. I have never paid any attention to projections because I know that they are flawed and that their origin basically comes from a guessing game or agenda.
Trump won, I get it. Enjoy the living fuck out of it...seriously. The conversation we are having isn't about Trump...and you don't seem to see that.
I'm just using Trump winning as an evidence based fact steeped by opposing projections and statistics. As opposed to anyone providing a clear and concrete example of a female making less than a male in the same job. Anyone?
Even if I (or anyone else) did, it probably wouldn't matter. Your logic is flawed. Thank you for reminding me why I do not respond to your posts. That wasn't sarcasm, by the way. Thank you!
Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
Right....so starting a thread about personally experiencing sexism but won't elaborate? What is the point of the thread?
the point of the thread wasn't about personal experience, but it may have been what inspired the need to post about the topic. from what I know of Kat, you won't receive the answer you seek. Nor should you expect to.
it is a FACT that women make about 70% of the wages men do for doing the same job. if that isn't enough in and of itself, I don't know what is.
if YOU made 7/10 of what a woman made at what you do, for no other reason than your gender, damn right you'd be pissed about it, don't you think?
I hear what you are saying. I just don't get that all these women and proponent males of their voice who say they make less but don't give concrete examples other than statistics and graphs.
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.
I know how to read a graph of statistics. The one posted above does not mean anything to anyone. It is merely numbers and mean as much as the polls that showed Hillary was a shoe in.
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your first point - Are you saying that a female in the USA will make less statistically at say Starbucks?, insert any restaurant name etc.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
statistics are meaningless? you don't like facts when it doesn't suit your opinion?
why the obsession with starbucks and hospitality? no one is referring to entry level jobs that require little skill. we are talking about professions here.
"Oh Canada...you're beautiful when you're drunk" -EV 8/14/93
Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
Right....so starting a thread about personally experiencing sexism but won't elaborate? What is the point of the thread?
the point of the thread wasn't about personal experience, but it may have been what inspired the need to post about the topic. from what I know of Kat, you won't receive the answer you seek. Nor should you expect to.
it is a FACT that women make about 70% of the wages men do for doing the same job. if that isn't enough in and of itself, I don't know what is.
if YOU made 7/10 of what a woman made at what you do, for no other reason than your gender, damn right you'd be pissed about it, don't you think?
I hear what you are saying. I just don't get that all these women and proponent males of their voice who say they make less but don't give concrete examples other than statistics and graphs.
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.
I know how to read a graph of statistics. The one posted above does not mean anything to anyone. It is merely numbers and mean as much as the polls that showed Hillary was a shoe in.
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your first point - Are you saying that a female in the USA will make less statistically at say Starbucks?, insert any restaurant name etc.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
1. You missed what I said & what I meant, and that's fine. 2. If you think that Projections (I'll spell this out for you...projections are basically G-U-E-S-S-ES) are the same as Statistics (which are based on F-A-C-T-S), then you are a bit more misguided than you may realize. I have never paid any attention to projections because I know that they are flawed and that their origin basically comes from a guessing game or agenda.
Trump won, I get it. Enjoy the living fuck out of it...seriously. The conversation we are having isn't about Trump...and you don't seem to see that.
I'm just using Trump winning as an evidence based fact steeped by opposing projections and statistics. As opposed to anyone providing a clear and concrete example of a female making less than a male in the same job. Anyone?
projections and statistics are completley different. I'm not sure why that's so complicated for you to understand.
yeah, um, you know, that, um, graph you said you knew how to read? that is a summary based on concrete examples. jesus.
"Oh Canada...you're beautiful when you're drunk" -EV 8/14/93
Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
Right....so starting a thread about personally experiencing sexism but won't elaborate? What is the point of the thread?
the point of the thread wasn't about personal experience, but it may have been what inspired the need to post about the topic. from what I know of Kat, you won't receive the answer you seek. Nor should you expect to.
it is a FACT that women make about 70% of the wages men do for doing the same job. if that isn't enough in and of itself, I don't know what is.
if YOU made 7/10 of what a woman made at what you do, for no other reason than your gender, damn right you'd be pissed about it, don't you think?
I hear what you are saying. I just don't get that all these women and proponent males of their voice who say they make less but don't give concrete examples other than statistics and graphs.
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.
I know how to read a graph of statistics. The one posted above does not mean anything to anyone. It is merely numbers and mean as much as the polls that showed Hillary was a shoe in.
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your first point - Are you saying that a female in the USA will make less statistically at say Starbucks?, insert any restaurant name etc.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
1. You missed what I said & what I meant, and that's fine. 2. If you think that Projections (I'll spell this out for you...projections are basically G-U-E-S-S-ES) are the same as Statistics (which are based on F-A-C-T-S), then you are a bit more misguided than you may realize. I have never paid any attention to projections because I know that they are flawed and that their origin basically comes from a guessing game or agenda.
Trump won, I get it. Enjoy the living fuck out of it...seriously. The conversation we are having isn't about Trump...and you don't seem to see that.
I'm just using Trump winning as an evidence based fact steeped by opposing projections and statistics. As opposed to anyone providing a clear and concrete example of a female making less than a male in the same job. Anyone?
First, all facts are evidence-based. No need to add that qualifier, as without evidence, facts are just opinions.
Next, statistics are the summary of facts gathered from a consistent demographic of entities (i.e. American women), either by extrapolating a sample's results to contain an entire demographic, or by collecting data of said entire demographic. To dispute female employment statistics is fairly outrageous, when they are produced by the government based on mandatory tax data provided. If you feel that a 30% pay disparity in full-time salaries is because the female gender are paid a proportion of their income untraceably, you are really out to lunch. If you feel that statistics as irrefutable as these do not represent clear and concrete examples of pay inequality, you are also out to lunch.
Finally, if a statistic is generated by sampling, one could argue that like a projection, extrapolations must occur, leaving room for inaccurate or disingenuous trending. When tax/census data are your sources, however, your extrapolation is minimal, and the two are not equatable.
In any case, either I've wasted my time because you're not capable of understanding why statistics with proper sources are factual, or because you're simply here as a contrarian.
'05 - TO, '06 - TO 1, '08 - NYC 1 & 2, '09 - TO, Chi 1 & 2, '10 - Buffalo, NYC 1 & 2, '11 - TO 1 & 2, Hamilton, '13 - Buffalo, Brooklyn 1 & 2, '15 - Global Citizen, '16 - TO 1 & 2, Chi 2
EV
Toronto Film Festival 9/11/2007, '08 - Toronto 1 & 2, '09 - Albany 1, '11 - Chicago 1
Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
Right....so starting a thread about personally experiencing sexism but won't elaborate? What is the point of the thread?
the point of the thread wasn't about personal experience, but it may have been what inspired the need to post about the topic. from what I know of Kat, you won't receive the answer you seek. Nor should you expect to.
it is a FACT that women make about 70% of the wages men do for doing the same job. if that isn't enough in and of itself, I don't know what is.
if YOU made 7/10 of what a woman made at what you do, for no other reason than your gender, damn right you'd be pissed about it, don't you think?
I hear what you are saying. I just don't get that all these women and proponent males of their voice who say they make less but don't give concrete examples other than statistics and graphs.
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.
I know how to read a graph of statistics. The one posted above does not mean anything to anyone. It is merely numbers and mean as much as the polls that showed Hillary was a shoe in.
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your first point - Are you saying that a female in the USA will make less statistically at say Starbucks?, insert any restaurant name etc.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
1. You missed what I said & what I meant, and that's fine. 2. If you think that Projections (I'll spell this out for you...projections are basically G-U-E-S-S-ES) are the same as Statistics (which are based on F-A-C-T-S), then you are a bit more misguided than you may realize. I have never paid any attention to projections because I know that they are flawed and that their origin basically comes from a guessing game or agenda.
Trump won, I get it. Enjoy the living fuck out of it...seriously. The conversation we are having isn't about Trump...and you don't seem to see that.
I'm just using Trump winning as an evidence based fact steeped by opposing projections and statistics. As opposed to anyone providing a clear and concrete example of a female making less than a male in the same job. Anyone?
First, all facts are evidence-based. No need to add that qualifier, as without evidence, facts are just opinions.
Next, statistics are the summary of facts gathered from a consistent demographic of entities (i.e. American women), either by extrapolating a sample's results to contain an entire demographic, or by collecting data of said entire demographic. To dispute female employment statistics is fairly outrageous, when they are produced by the government based on mandatory tax data provided. If you feel that a 30% pay disparity in full-time salaries is because the female gender are paid a proportion of their income untraceably, you are really out to lunch. If you feel that statistics as irrefutable as these do not represent clear and concrete examples of pay inequality, you are also out to lunch.
Finally, if a statistic is generated by sampling, one could argue that like a projection, extrapolations must occur, leaving room for inaccurate or disingenuous trending. When tax/census data are your sources, however, your extrapolation is minimal, and the two are not equatable.
In any case, either I've wasted my time because you're not capable of understanding why statistics with proper sources are factual, or because you're simply here as a contrarian.
Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
Right....so starting a thread about personally experiencing sexism but won't elaborate? What is the point of the thread?
the point of the thread wasn't about personal experience, but it may have been what inspired the need to post about the topic. from what I know of Kat, you won't receive the answer you seek. Nor should you expect to.
it is a FACT that women make about 70% of the wages men do for doing the same job. if that isn't enough in and of itself, I don't know what is.
if YOU made 7/10 of what a woman made at what you do, for no other reason than your gender, damn right you'd be pissed about it, don't you think?
I hear what you are saying. I just don't get that all these women and proponent males of their voice who say they make less but don't give concrete examples other than statistics and graphs.
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.
I know how to read a graph of statistics. The one posted above does not mean anything to anyone. It is merely numbers and mean as much as the polls that showed Hillary was a shoe in.
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your first point - Are you saying that a female in the USA will make less statistically at say Starbucks?, insert any restaurant name etc.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
1. You missed what I said & what I meant, and that's fine. 2. If you think that Projections (I'll spell this out for you...projections are basically G-U-E-S-S-ES) are the same as Statistics (which are based on F-A-C-T-S), then you are a bit more misguided than you may realize. I have never paid any attention to projections because I know that they are flawed and that their origin basically comes from a guessing game or agenda.
Trump won, I get it. Enjoy the living fuck out of it...seriously. The conversation we are having isn't about Trump...and you don't seem to see that.
I'm just using Trump winning as an evidence based fact steeped by opposing projections and statistics. As opposed to anyone providing a clear and concrete example of a female making less than a male in the same job. Anyone?
projections and statistics are completley different. I'm not sure why that's so complicated for you to understand.
yeah, um, you know, that, um, graph you said you knew how to read? that is a summary based on concrete examples. jesus.
You and @benjs hit the nail on the head...I thought that I was pretty clear. Apparently not. Lol.
^^^ I fail to see the concrete examples that make up the graph. It's just dots, lines, and statements. Am I missing a source link? I might as well just draw up an opposite of the same graph and leave it at that. No questions allowed, just a simple "accept the graph as fact and shut it", is really what some here are implying.
^^^ I fail to see the concrete examples that make up the graph. It's just dots, lines, and statements. Am I missing a source link? I might as well just draw up an opposite of the same graph and leave it at that. No questions allowed, just a simple "accept the graph as fact and shut it", is really what some here are implying.
You did not allude that this particular graph should be questioned - you equated projections with statistics (false - one is a prediction, the other is factual or extrapolated linearly based on fair sampling), and wrote both off as the opposite of evidence (also false - it is an aggregation of evidence).
As for the source, you're simply not using basic skills of observation. The source is clearly printed at the bottom of the graph, as is standard for graphs.
Since you can't be bothered to type those words into Google to get right to the source, here's the sampling information, with the full link at the bottom of my post:
"Source of Estimates The data in this report are from the 2016 Current Population Survey (CPS) Annual Social and Economic Supplement (ASEC) and were collected in the 50 states and the District of Columbia. The data do not represent residents of Puerto Rico and U.S. Island Areas.* The data are based on a sample of about 95,000 addresses. The estimates in this report are controlled to independent national population estimates by age, sex, race, and Hispanic origin for March 2016. Beginning with 2010, estimates are based on 2010 Census population counts and are updated annually taking into account births, deaths, emigra- tion, and immigration. The CPS is a household survey primarily used to collect employment data. The sample universe for the basic CPS consists of the resident civilian non- institutionalized population of the United States. People in institutions, such as prisons, long-term care hospitals, and nursing homes, are not eligible to be interviewed in the CPS. Students living in dormitories are included in the estimates only if information about them is reported in an interview at their parents’ home. Since the CPS is a household survey, people who are homeless and not living in shelters are not included in the sample. The sample universe for the CPS ASEC is slightly larger than that of the basic CPS since it includes military personnel who live in a household with at least one other civilian adult, regardless of whether they live off post or on post. All other Armed Forces are excluded. For further documentation about the CPS ASEC, see www2.census.gov/programs-surveys/cps/techdocs/cpsmar16.pdf.
Statistical Accuracy Most of the data from the CPS ASEC were collected in March (with some data collected in February and April). The estimates in this report (which may be shown in text, figures, and tables) are based on responses from a sample of the population and may differ from actual values because of sampling variability or other factors. As a result, apparent differences between the estimates for two or more groups may not be statistically significant. All comparative statements have undergone statistical testing and are significant at the 90 percent confidence level unless otherwise noted. In this report, the variances of estimates were calculated using both the Successive Difference Replication (SDR) method and the Generalized Variance Function (GVF) approach. (See Appendix C for a more extensive discussion of these methods.) Further information about the source and accuracy of the estimates is available at www2.census.gov/library /publications/2016/demo/p60-256sa.pdf.
State and Local Estimates of Income and Poverty The Census Bureau presents annual estimates of median household income and poverty by state and other smaller geographic units based on data collected in the American Community Survey (ACS). Single-year estimates are available for geographic units with populations of 65,000 or more. Estimates of income and poverty for all geographic units, includ- ing census tracts and block groups, are available by pooling 5 years of ACS data. The Census Bureau’s Small Area Income and Poverty Estimates (SAIPE) program produces annual estimates of a select set of income and poverty measures. Using statistical models, SAIPE produces estimates of median household income and poverty for states and all counties, as well as population and poverty estimates for school districts. The SAIPE approach combines data from a variety of sources, including administrative records, population estimates, the decennial census, and the ACS, to provide con- sistent and reliable single-year estimates. In general, SAIPE estimates have lower variances than ACS estimates but are released later because they incorporate ACS data in the models. The 2014 income and poverty estimates from this program are available at . Estimates for 2015 will be available later this year."
If you're going to refute statistics as non-factual, you're going to have to dispute the data collection techniques. Personally, when I see a 95,000 household statistic sample with a 90% confidence level, variances tested with two approaches, and well-documented breakdowns of the construction of the sample as well as the sources of error - my basic statistical understanding (several university-level statistics courses for a professional degree in Structural Engineering) tells me that this graph is far more than "dots, lines and statements".
To allude to the fact that pay inequity by gender is a myth, is both insulting and false. To insinuate that anyone here has suggested to "accept the graph and shut it" is also false.
^^^ I fail to see the concrete examples that make up the graph. It's just dots, lines, and statements. Am I missing a source link? I might as well just draw up an opposite of the same graph and leave it at that. No questions allowed, just a simple "accept the graph as fact and shut it", is really what some here are implying.
You did not allude that this particular graph should be questioned - you equated projections with statistics (false - one is a prediction, the other is factual or extrapolated linearly based on fair sampling), and wrote both off as the opposite of evidence (also false - it is an aggregation of evidence).
As for the source, you're simply not using basic skills of observation. The source is clearly printed at the bottom of the graph, as is standard for graphs.
Since you can't be bothered to type those words into Google to get right to the source, here's the sampling information, with the full link at the bottom of my post:
"Source of Estimates The data in this report are from the 2016 Current Population Survey (CPS) Annual Social and Economic Supplement (ASEC) and were collected in the 50 states and the District of Columbia. The data do not represent residents of Puerto Rico and U.S. Island Areas.* The data are based on a sample of about 95,000 addresses. The estimates in this report are controlled to independent national population estimates by age, sex, race, and Hispanic origin for March 2016. Beginning with 2010, estimates are based on 2010 Census population counts and are updated annually taking into account births, deaths, emigra- tion, and immigration. The CPS is a household survey primarily used to collect employment data. The sample universe for the basic CPS consists of the resident civilian non- institutionalized population of the United States. People in institutions, such as prisons, long-term care hospitals, and nursing homes, are not eligible to be interviewed in the CPS. Students living in dormitories are included in the estimates only if information about them is reported in an interview at their parents’ home. Since the CPS is a household survey, people who are homeless and not living in shelters are not included in the sample. The sample universe for the CPS ASEC is slightly larger than that of the basic CPS since it includes military personnel who live in a household with at least one other civilian adult, regardless of whether they live off post or on post. All other Armed Forces are excluded. For further documentation about the CPS ASEC, see www2.census.gov/programs-surveys/cps/techdocs/cpsmar16.pdf.
Statistical Accuracy Most of the data from the CPS ASEC were collected in March (with some data collected in February and April). The estimates in this report (which may be shown in text, figures, and tables) are based on responses from a sample of the population and may differ from actual values because of sampling variability or other factors. As a result, apparent differences between the estimates for two or more groups may not be statistically significant. All comparative statements have undergone statistical testing and are significant at the 90 percent confidence level unless otherwise noted. In this report, the variances of estimates were calculated using both the Successive Difference Replication (SDR) method and the Generalized Variance Function (GVF) approach. (See Appendix C for a more extensive discussion of these methods.) Further information about the source and accuracy of the estimates is available at www2.census.gov/library /publications/2016/demo/p60-256sa.pdf.
State and Local Estimates of Income and Poverty The Census Bureau presents annual estimates of median household income and poverty by state and other smaller geographic units based on data collected in the American Community Survey (ACS). Single-year estimates are available for geographic units with populations of 65,000 or more. Estimates of income and poverty for all geographic units, includ- ing census tracts and block groups, are available by pooling 5 years of ACS data. The Census Bureau’s Small Area Income and Poverty Estimates (SAIPE) program produces annual estimates of a select set of income and poverty measures. Using statistical models, SAIPE produces estimates of median household income and poverty for states and all counties, as well as population and poverty estimates for school districts. The SAIPE approach combines data from a variety of sources, including administrative records, population estimates, the decennial census, and the ACS, to provide con- sistent and reliable single-year estimates. In general, SAIPE estimates have lower variances than ACS estimates but are released later because they incorporate ACS data in the models. The 2014 income and poverty estimates from this program are available at . Estimates for 2015 will be available later this year."
If you're going to refute statistics as non-factual, you're going to have to dispute the data collection techniques. Personally, when I see a 95,000 household statistic sample with a 90% confidence level, variances tested with two approaches, and well-documented breakdowns of the construction of the sample as well as the sources of error - my basic statistical understanding (several university-level statistics courses for a professional degree in Structural Engineering) tells me that this graph is far more than "dots, lines and statements".
To allude to the fact that pay inequity by gender is a myth, is both insulting and false. To insinuate that anyone here has suggested to "accept the graph and shut it" is also false.
Nice post above Benjs I was wrong, I just scrolled down a little and the source on the graph was there. The reason I went off on it was because I was wondering why people weren't agreeing that it was just numbers and lines with no examples or a source. I see it now as I only looked at it once initially. So yes Benjs thanks for that and I still think that even with the source that the pay inequity is not as large as some people make it out to be.
Nice post above Benjs I was wrong, I just scrolled down a little and the source on the graph was there. The reason I went off on it was because I was wondering why people weren't agreeing that it was just numbers and lines with no examples or a source. I see it now as I only looked at it once initially. So yes Benjs thanks for that and I still think that even with the source that the pay inequity is not as large as some people make it out to be.
On what grounds would you like to question the data above?
'05 - TO, '06 - TO 1, '08 - NYC 1 & 2, '09 - TO, Chi 1 & 2, '10 - Buffalo, NYC 1 & 2, '11 - TO 1 & 2, Hamilton, '13 - Buffalo, Brooklyn 1 & 2, '15 - Global Citizen, '16 - TO 1 & 2, Chi 2
EV
Toronto Film Festival 9/11/2007, '08 - Toronto 1 & 2, '09 - Albany 1, '11 - Chicago 1
Nice post above Benjs I was wrong, I just scrolled down a little and the source on the graph was there. The reason I went off on it was because I was wondering why people weren't agreeing that it was just numbers and lines with no examples or a source. I see it now as I only looked at it once initially. So yes Benjs thanks for that and I still think that even with the source that the pay inequity is not as large as some people make it out to be.
On what grounds would you like to question the data above?
On the grounds that your honesty states my basic statistical understanding (several university-level statistics courses for a professional degree in Structural Engineering) tells me that this graph is far more than "dots, lines and statements".
As a layperson I don't necessarily understand the reasoning of a census especially by phone. In fact one let alone many could treat such calls as spam and give skewed results. I remember in the day telling telemarketers I was an astronaut and made 35K on my rotary phone. Imagine the fun I have now when such a person calls me. So I understand the source but I just do not meet or see anyone in the flesh stating that as a female they make less than a male doing the same task. Celebs excluded.
Nice post above Benjs I was wrong, I just scrolled down a little and the source on the graph was there. The reason I went off on it was because I was wondering why people weren't agreeing that it was just numbers and lines with no examples or a source. I see it now as I only looked at it once initially. So yes Benjs thanks for that and I still think that even with the source that the pay inequity is not as large as some people make it out to be.
On what grounds would you like to question the data above?
On the grounds that your honesty states my basic statistical understanding (several university-level statistics courses for a professional degree in Structural Engineering) tells me that this graph is far more than "dots, lines and statements".
As a layperson I don't necessarily understand the reasoning of a census especially by phone. In fact one let alone many could treat such calls as spam and give skewed results. I remember in the day telling telemarketers I was an astronaut and made 35K on my rotary phone. Imagine the fun I have now when such a person calls me. So I understand the source but I just do not meet or see anyone in the flesh stating that as a female they make less than a male doing the same task. Celebs excluded.
Dang, you've been trolling that long? An analog troll in a digital world, or a digital troll ahead of his day?
Nice post above Benjs I was wrong, I just scrolled down a little and the source on the graph was there. The reason I went off on it was because I was wondering why people weren't agreeing that it was just numbers and lines with no examples or a source. I see it now as I only looked at it once initially. So yes Benjs thanks for that and I still think that even with the source that the pay inequity is not as large as some people make it out to be.
On what grounds would you like to question the data above?
As a layperson I don't necessarily understand
You could have stopped right there.
Census collects data a number of ways, not just phone calls. Including door-to-door visits, industrial classifications, and state tax & finance records.
Giving false data is just another example of how you are an outlier that should be thrown out from the data set.
Nice post above Benjs I was wrong, I just scrolled down a little and the source on the graph was there. The reason I went off on it was because I was wondering why people weren't agreeing that it was just numbers and lines with no examples or a source. I see it now as I only looked at it once initially. So yes Benjs thanks for that and I still think that even with the source that the pay inequity is not as large as some people make it out to be.
On what grounds would you like to question the data above?
On the grounds that your honesty states my basic statistical understanding (several university-level statistics courses for a professional degree in Structural Engineering) tells me that this graph is far more than "dots, lines and statements".
As a layperson I don't necessarily understand the reasoning of a census especially by phone. In fact one let alone many could treat such calls as spam and give skewed results. I remember in the day telling telemarketers I was an astronaut and made 35K on my rotary phone. Imagine the fun I have now when such a person calls me. So I understand the source but I just do not meet or see anyone in the flesh stating that as a female they make less than a male doing the same task. Celebs excluded.
I'd encourage looking through the links posted about data collection and error correction methods used. Some involve math, others are much more straightforward, such as 51,000 of the 95,000 households involving interviews. Many are also asked over the span of four months, given an eight months break, and asked the same questions again. Given the survey is hundreds of questions long, they're able to identify answers which have changed dramatically over this time span, which is used to gauge the reliability of the responses.
As an aside, I also don't think that anecdotal evidence when told by a victim or witness of an action is above lying, so maybe you should question everything rather than just what's convenient to your arguments.
'05 - TO, '06 - TO 1, '08 - NYC 1 & 2, '09 - TO, Chi 1 & 2, '10 - Buffalo, NYC 1 & 2, '11 - TO 1 & 2, Hamilton, '13 - Buffalo, Brooklyn 1 & 2, '15 - Global Citizen, '16 - TO 1 & 2, Chi 2
EV
Toronto Film Festival 9/11/2007, '08 - Toronto 1 & 2, '09 - Albany 1, '11 - Chicago 1
A great issue and it reminded me of Raju, the elephant in India who shed tears at being rescued from a horrible existence. He had chains on his ankles that became embedded in his skin and had to be removed. I keep up on his progress...it was such a sad and also happy story. He's doing great now. This movie about the ivory poaching sounds good...again, a great issue to get behind.
We probably would be in a position where our politicians just talked a lot, blamed the other party and nothing got done....oh wait.....
But at least we'd have less tweets, kids could actually learn a bit about real US history if the president decided to speak about it, and...I assuming a bit on this one...there would have been less presidential golf played. Oh and Bill Clinton would be getting BJs in the white house instead of at Ihop.
If she did this maybe I would have reconsidered my vote, this would have been great, I may have looked past all her flaws and crookedness.
Her question to America during the second debate: "Well, what would you do? Do you stay calm, keep smiling and carry on as if he weren't repeatedly invading your space? Or do you turn, look him in the eye and say loudly and clearly: 'Back up you creep, get away from me. I know you love to intimidate women, but you can't intimidate me, so back up.'"
Hilliary reflects on her interactions with Trump and admits she should have said or done something instead of nothing and so did Comey admit the same. Is there anyone else Im forgetting?
If she did this maybe I would have reconsidered my vote, this would have been great, I may have looked past all her flaws and crookedness.
Her question to America during the second debate: "Well, what would you do? Do you stay calm, keep smiling and carry on as if he weren't repeatedly invading your space? Or do you turn, look him in the eye and say loudly and clearly: 'Back up you creep, get away from me. I know you love to intimidate women, but you can't intimidate me, so back up.'"
Hilliary reflects on her interactions with Trump and admits she should have said or done something instead of nothing and so did Comey admit the same. Is there anyone else Im forgetting?
Ironic, isn’t it? A young woman who went to Yale Law and as a staffer, contributed to the resignation of Nixon. Ironic, isn’t it, that this same woman would give her life to bettering the average person, not by glad handing or smarmy smoke and mirror rhetoric like trickle down but with policy, proposals, legislation, down in the trenches, support of laws that help the unwashed masses. Ironic, isn’t it, that a woman who rose to such lofty heights, rising from forcing a man from office for clear violations of law, impeachable, released 20 years of tax returns for public scrutiny. Ironic, isn’t it, that Hillary was well known on the Hill for being well prepared, having done her homework, knew the issues inside and out, and was likeable. Ironic isn’t it, that after 30 years of investigation and scrutiny and only to be cheated out of what was deservedly hers, by almost 3 million votes, she’ll witness another disgraceful failure by a man who thought he knew better? Ironic, isn’t it, that her bookends to an illustrious career of serving the common good ends with Team Trump Treason? Over email and greed? Ironic, isn’t it?
Comments
2. If you think that Projections (I'll spell this out for you...projections are basically G-U-E-S-S-ES) are the same as Statistics (which are based on F-A-C-T-S), then you are a bit more misguided than you may realize. I have never paid any attention to projections because I know that they are flawed and that their origin basically comes from a guessing game or agenda.
Trump won, I get it. Enjoy the living fuck out of it...seriously. The conversation we are having isn't about Trump...and you don't seem to see that.
www.cluthelee.com
www.cluthe.com
As opposed to anyone providing a clear and concrete example of a female making less than a male in the same job.
Anyone?
Have a fantastic night.
www.cluthelee.com
www.cluthe.com
You too my fair-weather friend.
why the obsession with starbucks and hospitality? no one is referring to entry level jobs that require little skill. we are talking about professions here.
-EV 8/14/93
yeah, um, you know, that, um, graph you said you knew how to read? that is a summary based on concrete examples. jesus.
-EV 8/14/93
Next, statistics are the summary of facts gathered from a consistent demographic of entities (i.e. American women), either by extrapolating a sample's results to contain an entire demographic, or by collecting data of said entire demographic. To dispute female employment statistics is fairly outrageous, when they are produced by the government based on mandatory tax data provided. If you feel that a 30% pay disparity in full-time salaries is because the female gender are paid a proportion of their income untraceably, you are really out to lunch. If you feel that statistics as irrefutable as these do not represent clear and concrete examples of pay inequality, you are also out to lunch.
Finally, if a statistic is generated by sampling, one could argue that like a projection, extrapolations must occur, leaving room for inaccurate or disingenuous trending. When tax/census data are your sources, however, your extrapolation is minimal, and the two are not equatable.
In any case, either I've wasted my time because you're not capable of understanding why statistics with proper sources are factual, or because you're simply here as a contrarian.
EV
Toronto Film Festival 9/11/2007, '08 - Toronto 1 & 2, '09 - Albany 1, '11 - Chicago 1
www.cluthelee.com
www.cluthe.com
I fail to see the concrete examples that make up the graph.
It's just dots, lines, and statements. Am I missing a source link?
I might as well just draw up an opposite of the same graph and leave it at that.
No questions allowed, just a simple "accept the graph as fact and shut it", is really what some here are implying.
www.cluthelee.com
www.cluthe.com
As for the source, you're simply not using basic skills of observation. The source is clearly printed at the bottom of the graph, as is standard for graphs.
Since you can't be bothered to type those words into Google to get right to the source, here's the sampling information, with the full link at the bottom of my post:
"Source of Estimates
The data in this report are from the 2016 Current Population Survey (CPS) Annual Social and Economic Supplement (ASEC) and were collected in the 50 states and the District of Columbia. The data do not represent residents of Puerto Rico and U.S. Island Areas.* The data are based on a sample of about 95,000 addresses. The estimates in this report are controlled to independent national population estimates by age, sex, race, and Hispanic origin for March 2016. Beginning with 2010, estimates are based on 2010 Census population counts and are updated annually taking into account births, deaths, emigra- tion, and immigration.
The CPS is a household survey primarily used to collect employment data. The sample universe for the basic CPS consists of the resident civilian non- institutionalized population of the United States. People in institutions, such as prisons, long-term care hospitals, and nursing homes, are not eligible to be interviewed in the CPS. Students living in dormitories are included in the estimates only if information about them is reported in an interview at their parents’ home. Since the CPS is a household survey, people who are homeless and not living in shelters are not included in the sample. The sample universe for the CPS ASEC is slightly larger than that of the basic CPS since it includes military personnel who live in a household with at least one other civilian adult, regardless of whether they live off post or on post. All other Armed Forces are excluded. For further documentation about the CPS ASEC, see www2.census.gov/programs-surveys/cps/techdocs/cpsmar16.pdf.
Statistical Accuracy
Most of the data from the CPS ASEC were collected in March (with some data collected in February and April). The estimates in this report (which may be shown in text, figures, and tables) are based on responses from a sample of the population and may differ from actual values because of sampling variability or other factors. As a result, apparent differences between the estimates for two or more groups may not be statistically significant. All comparative statements have undergone statistical testing and are significant at the 90 percent confidence level unless otherwise noted. In this report, the variances of estimates were calculated using both the Successive Difference Replication (SDR) method and the Generalized Variance Function (GVF) approach. (See Appendix C for a more extensive discussion of these methods.) Further information about the source and accuracy of the estimates is available at www2.census.gov/library /publications/2016/demo/p60-256sa.pdf.
State and Local Estimates of Income and Poverty
The Census Bureau presents annual estimates of median household income and poverty by state and other smaller geographic units based on data collected in the American Community Survey (ACS). Single-year estimates are available for geographic units with populations of 65,000 or more. Estimates of income and poverty for all geographic units, includ- ing census tracts and block groups, are available by pooling 5 years of ACS data.
The Census Bureau’s Small Area Income and Poverty Estimates (SAIPE) program produces annual estimates of a select set of income and poverty measures. Using statistical models, SAIPE produces estimates of median household income and poverty for states and all counties, as well as population and poverty estimates for school districts. The SAIPE approach combines data from a variety of sources, including administrative records, population estimates, the decennial census, and the ACS, to provide con- sistent and reliable single-year estimates. In general, SAIPE estimates have lower variances than ACS estimates but are released later because they incorporate ACS data in the models.
The 2014 income and poverty estimates from this program are available at . Estimates for 2015 will be available later this year."
If you're going to refute statistics as non-factual, you're going to have to dispute the data collection techniques. Personally, when I see a 95,000 household statistic sample with a 90% confidence level, variances tested with two approaches, and well-documented breakdowns of the construction of the sample as well as the sources of error - my basic statistical understanding (several university-level statistics courses for a professional degree in Structural Engineering) tells me that this graph is far more than "dots, lines and statements".
To allude to the fact that pay inequity by gender is a myth, is both insulting and false. To insinuate that anyone here has suggested to "accept the graph and shut it" is also false.
https://www.census.gov/content/dam/Census/library/publications/2016/demo/p60-256.pdf
EV
Toronto Film Festival 9/11/2007, '08 - Toronto 1 & 2, '09 - Albany 1, '11 - Chicago 1
www.cluthelee.com
www.cluthe.com
Libtardaplorable©. And proud of it.
Brilliantati©
I was wrong, I just scrolled down a little and the source on the graph was there.
The reason I went off on it was because I was wondering why people weren't agreeing that it was just numbers and lines with no examples or a source. I see it now as I only looked at it once initially.
So yes Benjs thanks for that and I still think that even with the source that the pay inequity is not as large as some people make it out to be.
EV
Toronto Film Festival 9/11/2007, '08 - Toronto 1 & 2, '09 - Albany 1, '11 - Chicago 1
As a layperson I don't necessarily understand the reasoning of a census especially by phone.
In fact one let alone many could treat such calls as spam and give skewed results.
I remember in the day telling telemarketers I was an astronaut and made 35K on my rotary phone.
Imagine the fun I have now when such a person calls me.
So I understand the source but I just do not meet or see anyone in the flesh stating that as a female they make less than a male doing the same task.
Celebs excluded.
An analog troll in a digital world, or a digital troll ahead of his day?
Census collects data a number of ways, not just phone calls. Including door-to-door visits, industrial classifications, and state tax & finance records.
Giving false data is just another example of how you are an outlier that should be thrown out from the data set.
As an aside, I also don't think that anecdotal evidence when told by a victim or witness of an action is above lying, so maybe you should question everything rather than just what's convenient to your arguments.
EV
Toronto Film Festival 9/11/2007, '08 - Toronto 1 & 2, '09 - Albany 1, '11 - Chicago 1
Former Secretary of State talks about efforts made to prevent elephant poaching at 'The Protectors' screening
http://www.rollingstone.com/movies/news/watch-hillary-clinton-make-surprise-appearance-at-tribeca-w478326
A great issue and it reminded me of Raju, the elephant in India who shed tears at being rescued from a horrible existence. He had chains on his ankles that became embedded in his skin and had to be removed. I keep up on his progress...it was such a sad and also happy story. He's doing great now. This movie about the ivory poaching sounds good...again, a great issue to get behind.
Makes me wonder what could have been.
-EV 8/14/93
But at least we'd have less tweets, kids could actually learn a bit about real US history if the president decided to speak about it, and...I assuming a bit on this one...there would have been less presidential golf played. Oh and Bill Clinton would be getting BJs in the white house instead of at Ihop.
http://hosted.ap.org/dynamic/stories/E/EU_EUROPE_MIGRANTS_THE_LATEST?SITE=AP&SECTION=HOME&TEMPLATE=DEFAULT&CTIME=2017-07-03-07-30-35
If she did this maybe I would have reconsidered my vote, this would have been great, I may have looked past all her flaws and crookedness.
Her question to America during the second debate: "Well, what would you do? Do you stay calm, keep smiling and carry on as if he weren't repeatedly invading your space? Or do you turn, look him in the eye and say loudly and clearly: 'Back up you creep, get away from me. I know you love to intimidate women, but you can't intimidate me, so back up.'"
Hilliary reflects on her interactions with Trump and admits she should have said or done something instead of nothing and so did Comey admit the same. Is there anyone else Im forgetting?
http://www.motherjones.com/media/2017/08/hillary-clinton-my-skin-crawled-as-donald-trump-stalked-me-on-debate-stage/
Libtardaplorable©. And proud of it.
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