DBT
Contributor
Meanwhile, those at the top of the heap take the lions share, leave the scraps, call it 'trickle down economics' and slap each other on the backs in good fellowship.
Foot, meet bullet. From your own source they figure the estimate has a 90% chance of being within 300,000 of the correct value. That translates to somewhere between 2% and 4% error. In other words, between one and two digits of precision which is exactly what I have been saying.Educate yourself - How is unemployment data collected? - because you are unsuprisingly misinformed.
Normal data standards say that you report the precision you have. We see one digit past the decimal place--that's all they have and it's not perfectly solid as evidenced by how often it's revised later.
Your obsession with significant digits is fascinating because it misses the point - the actual of number of unemployed is estimated. It is accepted as the one of the best labor force estimates on the planet in terms of methodology.
Your reasoning is based on a misunderstanding of statistics and poor readoning The 90% confidence interval does not mean there is any necessary error or imprecision in measurement. It means that the sample my estimate may differ from a complete census.Foot, meet bullet. From your own source they figure the estimate has a 90% chance of being within 300,000 of the correct value. That translates to somewhere between 2% and 4% error. In other words, between one and two digits of precision which is exactly what I have been saying.Educate yourself - How is unemployment data collected? - because you are unsuprisingly misinformed.
Normal data standards say that you report the precision you have. We see one digit past the decimal place--that's all they have and it's not perfectly solid as evidenced by how often it's revised later.
Your obsession with significant digits is fascinating because it misses the point - the actual of number of unemployed is estimated. It is accepted as the one of the best labor force estimates on the planet in terms of methodology.
Since minimum wage workers are about 1% of the population it should be apparent that unemployment of minimum wage workers has a fraction of a digit of negative precision--in other words, it's meaningless.
Reality 101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?Your reasoning is based on a misunderstanding of statistics and poor readoning The 90% confidence interval does not mean there is any necessary error or imprecision in measurement. It means that the sample my estimate may differ from a complete census.Foot, meet bullet. From your own source they figure the estimate has a 90% chance of being within 300,000 of the correct value. That translates to somewhere between 2% and 4% error. In other words, between one and two digits of precision which is exactly what I have been saying.Educate yourself - How is unemployment data collected? - because you are unsuprisingly misinformed.
Normal data standards say that you report the precision you have. We see one digit past the decimal place--that's all they have and it's not perfectly solid as evidenced by how often it's revised later.
Your obsession with significant digits is fascinating because it misses the point - the actual of number of unemployed is estimated. It is accepted as the one of the best labor force estimates on the planet in terms of methodology.
Since minimum wage workers are about 1% of the population it should be apparent that unemployment of minimum wage workers has a fraction of a digit of negative precision--in other words, it's meaningless.
A change that was within the confidence interval would not be seen.Moreover, the notion that changes in unemployment would not necessarily be captured is ludicrous.
No--that's a common error of the advocates of raising the minimum wage. It's actually the value for at or below the minimum wage. The only way a normal employee can be below minimum wage is if they are tipped. And tipped workers typically end up above minimum wage, often well above it. The demographics of the "or below" group also is very different than for the "at" group.BTW, the estimates for workers earning the federal minimum wage or below is closer to 2%. Since some states have minimum wages above the federal minimum, it is possible the number is even higher.
Finally, the point you persistently avoid is there are studies based on a complete census if s region .
I presume that saditics are statistics that make one sad?Did you never take probability and saditics?
Nope, never “took” any statistics or higher math. But I was given to understand confidence intervals as limits to the range of possible error, not an assurance that such error must exist. So if there is a value of 20 put forth for “x” with a 95% confidence interval, the actual value of “x”COULD be 19 or 21, but it’s not101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?
How “typically”? I hear lots of them saying that for every shift that nets them $50/hr, there are thirty shifts that net them $4/hr or similar. But since you object to stats that contain confidence intervals, you must surely be able to evidence your assertion with unassailable facts sans any error bars or confidence intervals, right?tipped workers typically end up above minimum wage
. i teach it. You are wrong. A confidence interval has nothing to do with the precision of measurement. The point estimate is precise and an unbiased estimate of the underlying population parameter.Reality 101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?Your reasoning is based on a misunderstanding of statistics and poor readoning The 90% confidence interval does not mean there is any necessary error or imprecision in measurement. It means that the sample my estimate may differ from a complete census.Foot, meet bullet. From your own source they figure the estimate has a 90% chance of being within 300,000 of the correct value. That translates to somewhere between 2% and 4% error. In other words, between one and two digits of precision which is exactly what I have been saying.Educate yourself - How is unemployment data collected? - because you are unsuprisingly misinformed.
Normal data standards say that you report the precision you have. We see one digit past the decimal place--that's all they have and it's not perfectly solid as evidenced by how often it's revised later.
Your obsession with significant digits is fascinating because it misses the point - the actual of number of unemployed is estimated. It is accepted as the one of the best labor force estimates on the planet in terms of methodology.
Since minimum wage workers are about 1% of the population it should be apparent that unemployment of minimum wage workers has a fraction of a digit of negative precision--in other words, it's meaningless.
. Utter nonsense. A properly taken new sample would very likely show it.Loren Pechtel said:A change that was within the confidence interval would not be seen.Moreover, the notion that changes in unemployment would not necessarily be captured is ludicrous.
You are wrong. There are exceptions to minimum wages that go beyond tipped workers.Loren Pechtel said:No--that's a common error of the advocates of raising the minimum wage. It's actually the value for at or below the minimum wage. The only way a normal employee can be below minimum wage is if they are tipped. And tipped workers typically end up above minimum wage, often well above it. The demographics of the "or below" group also is very different than for the "at" group.BTW, the estimates for workers earning the federal minimum wage or below is closer to 2%. Since some states have minimum wages above the federal minimum, it is possible the number is even higher.
Finally, the point you persistently avoid is there are studies based on a complete census if s region .
At the university I never heard anyone who had taken it refer to it by it's proper name.I presume that saditics are statistics that make one sad?Did you never take probability and saditics?
1) You're being a bit simple about it. A 95% confidence interval (also reported as p=.05) means that it's 95% likely that the value is within that range. It is not a certainty.Nope, never “took” any statistics or higher math. But I was given to understand confidence intervals as limits to the range of possible error, not an assurance that such error must exist. So if there is a value of 20 put forth for “x” with a 95% confidence interval, the actual value of “x”COULD be 19 or 21, but it’s not101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?
22 or higher, nor is it 18 or lower.
In my admittedly low level understanding, this does not render the evaluation useless - it gives a reliable range of possible values for “x”. But you are saying that the effect you seek to isolate must necessarily lie entirely within the error bar, correct?
Yet you blithely put forth blue sky projections pulled out of … ??
If they really were only getting $4/hr for thirty of the thirty-one shifts the employer would be in trouble with the labor department.How “typically”? I hear lots of them saying that for every shift that nets them $50/hr, there are thirty shifts that net them $4/hr or similar. But since you object to stats that contain confidence intervals, you must surely be able to evidence your assertion with unassailable facts sans any error bars or confidence intervals, right?tipped workers typically end up above minimum wage
I’m open to being entirely wrong about all of the above, but only if it can be shown where I have gone astray by expecting a degree of accuracy from you that you demand of others …
Estimate. Just because the value is precise doesn't mean the underlying value is exactly what the estimate says.. i teach it. You are wrong. A confidence interval has nothing to do with the precision of measurement. The point estimate is precise and an unbiased estimate of the underlying population parameter.Reality 101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?
Once again, showing that you don't actually understand. (And, why the class has that nickname--too many teachers of it don't actually understand.). Utter nonsense. A properly taken new sample would very likely show it.Loren Pechtel said:A change that was within the confidence interval would not be seen.Moreover, the notion that changes in unemployment would not necessarily be captured is ludicrous.
Note that I said "normal employee". I realize there are exceptions, I'm excluding them from the sample because they're small and have no bearing on the effect of raising the minimum wage anyway.You are wrong. There are exceptions to minimum wages that go beyond tipped workers.Loren Pechtel said:No--that's a common error of the advocates of raising the minimum wage. It's actually the value for at or below the minimum wage. The only way a normal employee can be below minimum wage is if they are tipped. And tipped workers typically end up above minimum wage, often well above it. The demographics of the "or below" group also is very different than for the "at" group.BTW, the estimates for workers earning the federal minimum wage or below is closer to 2%. Since some states have minimum wages above the federal minimum, it is possible the number is even higher.
Finally, the point you persistently avoid is there are studies based on a complete census if s region .
No--I pointed out the 2% figure is counting the wrong thing.And, of course, you missed the point that there are more minimum wage workers than you claim .
You twist everything I say and then claim contradictions that were not there.At this point, given your lack of relevant information and knowledge, along with your contradictory position that the effects of an increase in the minimum wage on employment are an unmeasurable empirical question it must be negative, indicate to this poster you that entire position is based on ignorance, illogic and belief.
Yeah, that’s how it is with undetectable effects.Rather, I'm showing that for a huge range of actual values the confidence interval will include zero.
1) You're being a bit simple about it. A 95% confidence interval (also reported as p=.05) means that it's 95% likely that the value is within that range. It is not a certainty.Nope, never “took” any statistics or higher math. But I was given to understand confidence intervals as limits to the range of possible error, not an assurance that such error must exist. So if there is a value of 20 put forth for “x” with a 95% confidence interval, the actual value of “x”COULD be 19 or 21, but it’s not101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?
22 or higher, nor is it 18 or lower.
In my admittedly low level understanding, this does not render the evaluation useless - it gives a reliable range of possible values for “x”. But you are saying that the effect you seek to isolate must necessarily lie entirely within the error bar, correct?
Yet you blithely put forth blue sky projections pulled out of … ??
2) The existence of an error range inherently says you are not certain of the exact value.
3) I'm not putting forth blue sky projections. Rather, I'm showing that for a huge range of actual values the confidence interval will include zero. I put a piece of paper on a scale--reads 0. Obviously paper is weightless! I can put quite a bit of paper on it (I'm thinking of the scale we weigh suitcases with) and it will still say zero. Thus you can't conclude that because the scale says zero that I have no paper.
How “typically”? I hear lots of them saying that for every shift that nets them $50/hr, there are thirty shifts that net them $4/hr or similar. But since you object to stats that contain confidence intervals, you must surely be able to evidence your assertion with unassailable facts sans any error bars or confidence intervals, right?tipped workers typically end up above minimum wage
I’m open to being entirely wrong about all of the above, but only if it can be shown where I have gone astray by expecting a degree of accuracy from you that you demand of others …
If they really were only getting $4/hr for thirty of the thirty-one shifts the employer would be in trouble with the labor department.
You are mistaken. A new estimate occurs every month with a new sample. A new sample means new data. It is ludicrous to think that a new sample with new data would not show a change in all cases if there was a change.Estimate. Just because the value is precise doesn't mean the underlying value is exactly what the estimate says.. i teach it. You are wrong. A confidence interval has nothing to do with the precision of measurement. The point estimate is precise and an unbiased estimate of the underlying population parameter.Reality 101: If you have a confidence interval then you have imprecision in your measurement. Did you never take probability and saditics?
It sounds like you're applying it to a spherical cow rather than looking at what it means in the real world.
Once again, showing that you don't actually understand. (And, why the class has that nickname--too many teachers of it don't actually understand.). Utter nonsense. A properly taken new sample would very likely show it.Loren Pechtel said:A change that was within the confidence interval would not be seen.Moreover, the notion that changes in unemployment would not necessarily be captured is ludicrous.
Ah, the special pleading case.Note that I said "normal employee". I realize there are exceptions, I'm excluding them from the sample because they're small and have no bearing on the effect of raising the minimum wage anyway.You are wrong. There are exceptions to minimum wages that go beyond tipped workers.Loren Pechtel said:No--that's a common error of the advocates of raising the minimum wage. It's actually the value for at or below the minimum wage. The only way a normal employee can be below minimum wage is if they are tipped. And tipped workers typically end up above minimum wage, often well above it. The demographics of the "or below" group also is very different than for the "at" group.BTW, the estimates for workers earning the federal minimum wage or below is closer to 2%. Since some states have minimum wages above the federal minimum, it is possible the number is even higher.
Finally, the point you persistently avoid is there are studies based on a complete census if s region .
First, you ignored the salient point that in a number of states there are workers earning the state minimum wage which EXCEEDS the federal minimum wage. Those workers are excluded from that 2%. Second, you provided absolutely no evidence to indicate that the 1% is the correct estimate for the federal min. wage earners.No--I pointed out the 2% figure is counting the wrong thing.And, of course, you missed the point that there are more minimum wage workers than you claim .
A handwaved complaint. Please point out what you believe is a twisted interpretation of your position.You twist everything I say and then claim contradictions that were not there.At this point, given your lack of relevant information and knowledge, along with your contradictory position that the effects of an increase in the minimum wage on employment are an unmeasurable empirical question it must be negative, indicate to this poster you that entire position is based on ignorance, illogic and belief.
That's pretty significant since thirty (30) States' MW exceed the federal MW.there are workers earning the state minimum wage which EXCEEDS the federal minimum wage. Those workers are excluded from that 2%
No!We have one data point that shows the extreme case causes harm
This has been shown repeatedly not to be the case.
You do not get to keep using it; It's gone, exploded, no longer a thing.
We have ZERO data points that show any harm at all.
You don't get to cite American Samoa as data, for the same reason that in a discussion of combustion, you don't get to cite Phlogiston in support of your position.
Continuing to use falsehoods as though they hadn't been soundly refuted, is the hallmark of religion and propaganda. Phlogiston doesn't explain fire; Russia didn't defeat Ukraine in 2022; American Samoa is not an example the effects of minimum wage increases.
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No, the only ones with more money to spend are those getting the artificial wage increase. Most of the poor have LESS real income because of the higher prices they must pay due to the higher labor cost resulting from higher MW.It also discounts the economic growth due to poor people having more money to spend.That discounts the workers replaced by automation and that discounts the businesses that close because they're no longer economic.
^ Someone is terminally confused.Most of the poor have LESS real income because of the higher prices they must pay due to the higher labor cost resulting from higher MW.
Okay, pedant. The American Samoa economy is not a reliable proxy for the economy of the United States of America.American Samoa most certainly is the USA, that's not the problem.
Shame how those dummokratz are eliminizing all them career puzzishins, huh?WTF, nine years as a pizza delivery driver?!