Hillary knows
Comments
-
1. You missed what I said & what I meant, and that's fine.PJfanwillneverleave1 said:
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.mfc2006 said:
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.PJfanwillneverleave1 said:
I know how to read a graph of statistics.mfc2006 said:
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.PJfanwillneverleave1 said:
I hear what you are saying.HughFreakingDillon said:
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.PJfanwillneverleave1 said:
Right....so starting a thread about personally experiencing sexism but won't elaborate?oftenreading said:Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
What is the point of the thread?
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 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.
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.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
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 LOVE MUSIC.
www.cluthelee.com
www.cluthe.com0 -
I'm just using Trump winning as an evidence based fact steeped by opposing projections and statistics.mfc2006 said:
1. You missed what I said & what I meant, and that's fine.PJfanwillneverleave1 said:
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.mfc2006 said:
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.PJfanwillneverleave1 said:
I know how to read a graph of statistics.mfc2006 said:
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.PJfanwillneverleave1 said:
I hear what you are saying.HughFreakingDillon said:
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.PJfanwillneverleave1 said:
Right....so starting a thread about personally experiencing sexism but won't elaborate?oftenreading said:Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
What is the point of the thread?
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 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.
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.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
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.
As opposed to anyone providing a clear and concrete example of a female making less than a male in the same job.
Anyone?0 -
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!PJfanwillneverleave1 said:
I'm just using Trump winning as an evidence based fact steeped by opposing projections and statistics.mfc2006 said:
1. You missed what I said & what I meant, and that's fine.PJfanwillneverleave1 said:
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.mfc2006 said:
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.PJfanwillneverleave1 said:
I know how to read a graph of statistics.mfc2006 said:
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.PJfanwillneverleave1 said:
I hear what you are saying.HughFreakingDillon said:
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.PJfanwillneverleave1 said:
Right....so starting a thread about personally experiencing sexism but won't elaborate?oftenreading said:Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
What is the point of the thread?
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 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.
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.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
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.
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.I LOVE MUSIC.
www.cluthelee.com
www.cluthe.com0 -
^^^
You too my fair-weather friend.0 -
statistics are meaningless? you don't like facts when it doesn't suit your opinion?PJfanwillneverleave1 said:
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.mfc2006 said:
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.PJfanwillneverleave1 said:
I know how to read a graph of statistics.mfc2006 said:
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.PJfanwillneverleave1 said:
I hear what you are saying.HughFreakingDillon said:
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.PJfanwillneverleave1 said:
Right....so starting a thread about personally experiencing sexism but won't elaborate?oftenreading said:Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
What is the point of the thread?
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 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.
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.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
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.Your boos mean nothing to me, for I have seen what makes you cheer0 -
projections and statistics are completley different. I'm not sure why that's so complicated for you to understand.PJfanwillneverleave1 said:
I'm just using Trump winning as an evidence based fact steeped by opposing projections and statistics.mfc2006 said:
1. You missed what I said & what I meant, and that's fine.PJfanwillneverleave1 said:
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.mfc2006 said:
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.PJfanwillneverleave1 said:
I know how to read a graph of statistics.mfc2006 said:
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.PJfanwillneverleave1 said:
I hear what you are saying.HughFreakingDillon said:
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.PJfanwillneverleave1 said:
Right....so starting a thread about personally experiencing sexism but won't elaborate?oftenreading said:Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
What is the point of the thread?
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 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.
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.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
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.
As opposed to anyone providing a clear and concrete example of a female making less than a male in the same job.
Anyone?
yeah, um, you know, that, um, graph you said you knew how to read? that is a summary based on concrete examples. jesus.
Your boos mean nothing to me, for I have seen what makes you cheer0 -
First, all facts are evidence-based. No need to add that qualifier, as without evidence, facts are just opinions.PJfanwillneverleave1 said:
I'm just using Trump winning as an evidence based fact steeped by opposing projections and statistics.mfc2006 said:
1. You missed what I said & what I meant, and that's fine.PJfanwillneverleave1 said:
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.mfc2006 said:
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.PJfanwillneverleave1 said:
I know how to read a graph of statistics.mfc2006 said:
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.PJfanwillneverleave1 said:
I hear what you are saying.HughFreakingDillon said:
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.PJfanwillneverleave1 said:
Right....so starting a thread about personally experiencing sexism but won't elaborate?oftenreading said:Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
What is the point of the thread?
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 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.
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.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
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.
As opposed to anyone providing a clear and concrete example of a female making less than a male in the same job.
Anyone?
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 10 -
Evidence based factbenjs said:
First, all facts are evidence-based. No need to add that qualifier, as without evidence, facts are just opinions.PJfanwillneverleave1 said:
I'm just using Trump winning as an evidence based fact steeped by opposing projections and statistics.mfc2006 said:
1. You missed what I said & what I meant, and that's fine.PJfanwillneverleave1 said:
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.mfc2006 said:
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.PJfanwillneverleave1 said:
I know how to read a graph of statistics.mfc2006 said:
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.PJfanwillneverleave1 said:
I hear what you are saying.HughFreakingDillon said:
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.PJfanwillneverleave1 said:
Right....so starting a thread about personally experiencing sexism but won't elaborate?oftenreading said:Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
What is the point of the thread?
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 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.
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.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
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.
As opposed to anyone providing a clear and concrete example of a female making less than a male in the same job.
Anyone?
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.
Monkey Driven, Call this Living?0 -
You and @benjs hit the nail on the head...I thought that I was pretty clear. Apparently not. Lol.HughFreakingDillon said:
projections and statistics are completley different. I'm not sure why that's so complicated for you to understand.PJfanwillneverleave1 said:
I'm just using Trump winning as an evidence based fact steeped by opposing projections and statistics.mfc2006 said:
1. You missed what I said & what I meant, and that's fine.PJfanwillneverleave1 said:
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.mfc2006 said:
I guarantee if you were a female that lived the the United States, it would sure as fuck mean something to you.PJfanwillneverleave1 said:
I know how to read a graph of statistics.mfc2006 said:
If you can't understand statistics....which are FACTS, then you probably never will understand the point of equal rights/pay in the workforce.PJfanwillneverleave1 said:
I hear what you are saying.HughFreakingDillon said:
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.PJfanwillneverleave1 said:
Right....so starting a thread about personally experiencing sexism but won't elaborate?oftenreading said:Personal explanations may be wanted but are certainly not needed before anyone starts a thread.
What is the point of the thread?
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 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.
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.
And to your final ridiculous point, the poll numbers were PROJECTIONS, not actual STATISTICS.
To your second point - Projections are as meaningless as statistics, I mean President Trump was supposed to be a loser remember?
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.
As opposed to anyone providing a clear and concrete example of a female making less than a male in the same job.
Anyone?
yeah, um, you know, that, um, graph you said you knew how to read? that is a summary based on concrete examples. jesus.I LOVE MUSIC.
www.cluthelee.com
www.cluthe.com0 -
^^^
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.
0 -
Good god.....haha.I LOVE MUSIC.
www.cluthelee.com
www.cluthe.com0 -
Graphs get a little messy when you try to graph stories instead of dots and lines.my small self... like a book amongst the many on a shelf0
-
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).PJfanwillneverleave1 said:^^^
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.
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'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 10 -
:clap:I LOVE MUSIC.
www.cluthelee.com
www.cluthe.com0 -
But, but, but Obama.benjs said:
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).PJfanwillneverleave1 said:^^^
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.
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.pdf09/15/1998 & 09/16/1998, Mansfield, MA; 08/29/00 08/30/00, Mansfield, MA; 07/02/03, 07/03/03, Mansfield, MA; 09/28/04, 09/29/04, Boston, MA; 09/22/05, Halifax, NS; 05/24/06, 05/25/06, Boston, MA; 07/22/06, 07/23/06, Gorge, WA; 06/27/2008, Hartford; 06/28/08, 06/30/08, Mansfield; 08/18/2009, O2, London, UK; 10/30/09, 10/31/09, Philadelphia, PA; 05/15/10, Hartford, CT; 05/17/10, Boston, MA; 05/20/10, 05/21/10, NY, NY; 06/22/10, Dublin, IRE; 06/23/10, Northern Ireland; 09/03/11, 09/04/11, Alpine Valley, WI; 09/11/11, 09/12/11, Toronto, Ont; 09/14/11, Ottawa, Ont; 09/15/11, Hamilton, Ont; 07/02/2012, Prague, Czech Republic; 07/04/2012 & 07/05/2012, Berlin, Germany; 07/07/2012, Stockholm, Sweden; 09/30/2012, Missoula, MT; 07/16/2013, London, Ont; 07/19/2013, Chicago, IL; 10/15/2013 & 10/16/2013, Worcester, MA; 10/21/2013 & 10/22/2013, Philadelphia, PA; 10/25/2013, Hartford, CT; 11/29/2013, Portland, OR; 11/30/2013, Spokane, WA; 12/04/2013, Vancouver, BC; 12/06/2013, Seattle, WA; 10/03/2014, St. Louis. MO; 10/22/2014, Denver, CO; 10/26/2015, New York, NY; 04/23/2016, New Orleans, LA; 04/28/2016 & 04/29/2016, Philadelphia, PA; 05/01/2016 & 05/02/2016, New York, NY; 05/08/2016, Ottawa, Ont.; 05/10/2016 & 05/12/2016, Toronto, Ont.; 08/05/2016 & 08/07/2016, Boston, MA; 08/20/2016 & 08/22/2016, Chicago, IL; 07/01/2018, Prague, Czech Republic; 07/03/2018, Krakow, Poland; 07/05/2018, Berlin, Germany; 09/02/2018 & 09/04/2018, Boston, MA; 09/08/2022, Toronto, Ont; 09/11/2022, New York, NY; 09/14/2022, Camden, NJ; 09/02/2023, St. Paul, MN; 05/04/2024 & 05/06/2024, Vancouver, BC; 05/10/2024, Portland, OR; 05/03/2025, New Orleans, LA;
Libtardaplorable©. And proud of it.
Brilliantati©0 -
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.
0 -
The Earth isn't as round as people make it out to be.0
-
On what grounds would you like to question the data above?PJfanwillneverleave1 said: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.'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 10 -
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".benjs said:
On what grounds would you like to question the data above?PJfanwillneverleave1 said: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.
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.0 -
Dang, you've been trolling that long?PJfanwillneverleave1 said:
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".benjs said:
On what grounds would you like to question the data above?PJfanwillneverleave1 said: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.
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?Monkey Driven, Call this Living?0
Categories
- All Categories
- 149K Pearl Jam's Music and Activism
- 110.1K The Porch
- 278 Vitalogy
- 35.1K Given To Fly (live)
- 3.5K Words and Music...Communication
- 39.2K Flea Market
- 39.2K Lost Dogs
- 58.7K Not Pearl Jam's Music
- 10.6K Musicians and Gearheads
- 29.1K Other Music
- 17.8K Poetry, Prose, Music & Art
- 1.1K The Art Wall
- 56.8K Non-Pearl Jam Discussion
- 22.2K A Moving Train
- 31.7K All Encompassing Trip
- 2.9K Technical Stuff and Help