I echo what Dave Kelsen said.

///snipped///

Being that you wish to nitpick the method used in the subject test, I would point out that what was described was a "method" NOT a "methodology"!!!!A common mistake used even by those somewhat familiar with scientific testing.

DaveD

If you simply figure out how much the engine used over the entire

See my comment above.

Dave D wrote:

Yes what the OZP was described was a method. But you apparently completely missed the point I was attempting to make. He is using the wrong methodology. Yes I did make the mistake of critiquing some of the methods also when I should have stayed with the main point which is that the OP is using wrong methodology. Attempting to make more than one point per posting tends to confuse the dim twitted.

The idea of using statistical analysis to solve what is really an accounting problem is the wrong methodology. Let me give an analogy. lets suppose you go to the grocery store and you put 42 items in your shopping cart. When you get to the checkout counter you tell the clerk that you are going to pick 17 items from the cart and through scientific statistical analysis of the 17 picked items you are going to determine how much you will pay the store. The clerk will inform you that is the wrong methodology (more likely the store will just call the cops). It doesn't matter if you argue that you are going to use well established statistical methods and that you are extremely knowledgeable in regards to scientific testing - the store will still insist that is a ridiculous way to approach the problem. The application of statistical analysis to solve what is a basic accounting problem is using the wrong methodology. In the OP's case the specific methods used also happen to be suspect, but even if the statistical methods weren't flawed the fact remains - he's not using the best methodology.

Once one has abandoned what is a ridiculously unreliable methodology for this problem then you can start to think about the specific methods one might choose to use. For instance, since the OP appears to be numerically challenged he could account for the oil consumed in the following way: He could keep all the containers that the oil comes in. Then at 3000 miles when he drains the oil he could carefully and thoroughly extract the oil from the oil pan and oil filter and put the used oil back in the original containers to the original level. After 42000 miles simply divide 42000 by the number of empty containers to determine that miles per quart number that he is looking for. No record keeping or paper work will be necessary. And my strong suspicion is he would arrive at a substantially different number than he is now.

-jim

Yes what the OZP was described was a method. But you apparently completely missed the point I was attempting to make. He is using the wrong methodology. Yes I did make the mistake of critiquing some of the methods also when I should have stayed with the main point which is that the OP is using wrong methodology. Attempting to make more than one point per posting tends to confuse the dim twitted.

The idea of using statistical analysis to solve what is really an accounting problem is the wrong methodology. Let me give an analogy. lets suppose you go to the grocery store and you put 42 items in your shopping cart. When you get to the checkout counter you tell the clerk that you are going to pick 17 items from the cart and through scientific statistical analysis of the 17 picked items you are going to determine how much you will pay the store. The clerk will inform you that is the wrong methodology (more likely the store will just call the cops). It doesn't matter if you argue that you are going to use well established statistical methods and that you are extremely knowledgeable in regards to scientific testing - the store will still insist that is a ridiculous way to approach the problem. The application of statistical analysis to solve what is a basic accounting problem is using the wrong methodology. In the OP's case the specific methods used also happen to be suspect, but even if the statistical methods weren't flawed the fact remains - he's not using the best methodology.

Once one has abandoned what is a ridiculously unreliable methodology for this problem then you can start to think about the specific methods one might choose to use. For instance, since the OP appears to be numerically challenged he could account for the oil consumed in the following way: He could keep all the containers that the oil comes in. Then at 3000 miles when he drains the oil he could carefully and thoroughly extract the oil from the oil pan and oil filter and put the used oil back in the original containers to the original level. After 42000 miles simply divide 42000 by the number of empty containers to determine that miles per quart number that he is looking for. No record keeping or paper work will be necessary. And my strong suspicion is he would arrive at a substantially different number than he is now.

-jim

wrote:

I recorded everything I found as precisely as possible. Nothing is "missing" from the dataset.

However, one record was questionable and was therefore not included: my very first properly-recorded check gave me a mileage of 2,200. This created an anomalous spike (that did not occur at any other point in the test). I therefore decided I'd done something wrong during that particular check, and excluded it from the results.

I recorded everything I found as precisely as possible. Nothing is "missing" from the dataset.

However, one record was questionable and was therefore not included: my very first properly-recorded check gave me a mileage of 2,200. This created an anomalous spike (that did not occur at any other point in the test). I therefore decided I'd done something wrong during that particular check, and excluded it from the results.

--

Tegger

Tegger

It was left out because I didn't think to put it in.

Part of my reasoning for posting this to Usenet and BITOG was to solicit others' opinions on the test, its methodology, and the report. These I have received (some a bit irascibly), so thanks for that.

I have updated the PDF to account for the issues that have been brought up here and in BITOG.

http://www.tegger.com/hondafaq/misc/graph-may28-10.pdf I had to clear my cache before the updated PDF would show up.

--

Tegger

Tegger

I didn't, unfortunately. See my reply to "jim".

I put the fresh oil into a graduated container and pour it into the engine from that. This way I can make certain I add exactly what the engine used. If my measuring and chart are correct, then a reading of x-milliliters low low ought to be exactly offset by the same amount added back in. And it is, so far as I can see.

--

Tegger

Tegger

This methodology means that there is not a need to do a linearity check, at least for this study.

I quoted what you wrote above at honda-tech.com . The threads are in the tech/misc and Acura Integra sections.

Aside, for those trying to post to the BITOG forum: I applied to join the BITOG forum almost a week ago and still have not been approved.

Try applying again.

--

Tegger

Tegger

On 6/5/2010 9:42 AM, jim wrote:

Hey Jim,

You are dissing a guy who has provided good information for me and others for quite a while here. Lay off of him. He does more work to make this newsgroup valuable than just about anyone else.

Tegger,

Please don't be discouraged by his dissing you. Every newsgoup has those who want to criticize without offering their own work for review.

I appreciate you time and effort here. I know there are many more who do.

Michael

Hey Jim,

You are dissing a guy who has provided good information for me and others for quite a while here. Lay off of him. He does more work to make this newsgroup valuable than just about anyone else.

Tegger,

Please don't be discouraged by his dissing you. Every newsgoup has those who want to criticize without offering their own work for review.

I appreciate you time and effort here. I know there are many more who do.

Michael

Michael wrote:

Another person heard from who is stupid and proud of it.

In case you haven't noticed I have been posting in response to idiots who think this study is brilliant. The OP who posted the study gave me the impression that maybe he wasn't of the same mind as you idiots are.

He wrote:

[quote] By "called-out", I meant I expected somebody to bring up the issue of measurement accuracy when reading off the dipstick. The entire work depends on that, of course. And nobody but you brought it up. That doesn't say much for BITOG, frankly. [end quote]

I responded to that because it seemed to indicate he actually was interested in why this methodology might be flawed.

The problem is actually much worse than just "the issue of measurement accuracy when reading off the dipstick". Besides the measurements just being slightly wrong, there are two additional problems that may compound or significantly magnify the initial measurement errors.

1) If the first dipstick reading happens to for some reason have a tendency to overestimate the amount of oil used, then the second reading will perforce have a tendency to underestimate the amount of oil used. This is because the first measurement determines how much make up oil is added. If your measurement tells you that you used .65 quarts but you really used only .5 quarts then that extra .15 that is added goes to the second measurement. If your first measurement is wrong in one direction it will tend to make the second measurement equally wrong in the opposite direction.

2) Averaging miles/quart for driving intervals of different lengths does not give an accurate average. Lets take some example numbers to see why:

A- drive 1000 mi .5 quarts down on the dipstick = 2000 mi/qt B- drive 1500 mi 1.2 quart down on the dipstick = 1250 mi/qt -------------------------------------------------------- Average of A and B = 1625 mi/qt

Now even if we pretend the measurements were dead nuts accurate what we have is 1.7 quarts used in 2500 miles which comes to 1470 miles per quart as the actual oil consumption. The 1625 is just a bogus number.

Calculating how much oil an engine uses isn't rocket science and certainly doesn't require complicated charts and complex calculations. I once owned a car that burned 600 miles per quart. I drove it for 250,000 miles and it used the same amount of oil during the whole time I had the car. I could predict within 20 miles when the dipstick would exactly reach the add line. It went about 800 miles on the first quart, then 600 miles thereafter. This was because when the oil was changed 5 quarts brought it to slightly above the full line. Adding oil when it hit the add mark brought it up to slightly below the full mark. Just like clockwork over and over that pattern repeated. I used a little thicker oil in summer but it didn't make a noticeable difference in the consumption pattern.

Another person heard from who is stupid and proud of it.

In case you haven't noticed I have been posting in response to idiots who think this study is brilliant. The OP who posted the study gave me the impression that maybe he wasn't of the same mind as you idiots are.

He wrote:

[quote] By "called-out", I meant I expected somebody to bring up the issue of measurement accuracy when reading off the dipstick. The entire work depends on that, of course. And nobody but you brought it up. That doesn't say much for BITOG, frankly. [end quote]

I responded to that because it seemed to indicate he actually was interested in why this methodology might be flawed.

The problem is actually much worse than just "the issue of measurement accuracy when reading off the dipstick". Besides the measurements just being slightly wrong, there are two additional problems that may compound or significantly magnify the initial measurement errors.

1) If the first dipstick reading happens to for some reason have a tendency to overestimate the amount of oil used, then the second reading will perforce have a tendency to underestimate the amount of oil used. This is because the first measurement determines how much make up oil is added. If your measurement tells you that you used .65 quarts but you really used only .5 quarts then that extra .15 that is added goes to the second measurement. If your first measurement is wrong in one direction it will tend to make the second measurement equally wrong in the opposite direction.

2) Averaging miles/quart for driving intervals of different lengths does not give an accurate average. Lets take some example numbers to see why:

A- drive 1000 mi .5 quarts down on the dipstick = 2000 mi/qt B- drive 1500 mi 1.2 quart down on the dipstick = 1250 mi/qt -------------------------------------------------------- Average of A and B = 1625 mi/qt

Now even if we pretend the measurements were dead nuts accurate what we have is 1.7 quarts used in 2500 miles which comes to 1470 miles per quart as the actual oil consumption. The 1625 is just a bogus number.

Calculating how much oil an engine uses isn't rocket science and certainly doesn't require complicated charts and complex calculations. I once owned a car that burned 600 miles per quart. I drove it for 250,000 miles and it used the same amount of oil during the whole time I had the car. I could predict within 20 miles when the dipstick would exactly reach the add line. It went about 800 miles on the first quart, then 600 miles thereafter. This was because when the oil was changed 5 quarts brought it to slightly above the full line. Adding oil when it hit the add mark brought it up to slightly below the full mark. Just like clockwork over and over that pattern repeated. I used a little thicker oil in summer but it didn't make a noticeable difference in the consumption pattern.

An initial check is taken before each test sequence.

But you're only using two data points. I suspect that, as the dataset grows ever larger, that the difference between your first method and your second will lessen greatly, and will eventually disappear. That's why sample-size is so critical to any sort of statistics.

--

Tegger

Tegger

Tegger wrote:

No sorry doesn't at all work that way. You claim to be trying to determine how much oil is being used on average. Your method arriving at that number is grossly unreliable. However your data is too spotty to actually estimate how inaccurate that method is for this data.

The correct method is easy. If you summed how much make up oil you added in total plus how much less than full it was at the time of oil change, you would get a number that represents the total consumption over the entire 42000 miles. You then make the calculation on that total consumption and total miles.

Try your method with the IRS. Tell them you are going to average dollars/day for various periods of income that you selected by some unknown criteria and in which some of them you earned a lot of money per day and some periods not so much per day and that you will use that average of those 17 dollars/day figures as an accurate measure of your annual income. The idea is so absurd that you probably will even get an IRS agent to laugh. You don't have a statistical problem to solve - you have an accounting problem and you are applying absurd accounting practices.

-jim

No sorry doesn't at all work that way. You claim to be trying to determine how much oil is being used on average. Your method arriving at that number is grossly unreliable. However your data is too spotty to actually estimate how inaccurate that method is for this data.

The correct method is easy. If you summed how much make up oil you added in total plus how much less than full it was at the time of oil change, you would get a number that represents the total consumption over the entire 42000 miles. You then make the calculation on that total consumption and total miles.

Try your method with the IRS. Tell them you are going to average dollars/day for various periods of income that you selected by some unknown criteria and in which some of them you earned a lot of money per day and some periods not so much per day and that you will use that average of those 17 dollars/day figures as an accurate measure of your annual income. The idea is so absurd that you probably will even get an IRS agent to laugh. You don't have a statistical problem to solve - you have an accounting problem and you are applying absurd accounting practices.

-jim

<snip>

You make some fair points.

I respond by posting my raw data. They are in an Excel file, here: <http://www.tegger.com/hondafaq/misc/oil_consumption_.xls

The first two columns give the actual miles driven during each test, and the actual observed amount of oil used during that test. (It must be noted that, in order to maintain consistency with the "reported" mileage, the oil amounts are slightly adjusted. i.e.: 0.622 is actually 0.6; 0.597 is also actually 0.6.)

I know you chose extremes in your example in order to make a point, but now, having

Remember that doing it my way, I get 1663 mi/qt. Doing it your way gets...what number?

--

Tegger

Tegger

Tegger wrote:

This Excel data does not even look like the same data as the PDF. For example, in your PDF file you have what is labeled a first reading at 321,771 miles and a second reading at 323,206 miles. That is an interval of 1435 miles. I don't see any interval in the Excel file that is even close to 1435. I see another 1st reading at 310,440 and a second reading at 311,635 which is an interval of 1195. But I see nothing in the excel file that corresponds with that number either. I'm sorry I don't know what to make of your data. I don't know if you have a lot of typos or arithmetic errors or if something else is going on.

I already told you the data is too spotty to actually know what the oil consumption might be to any reasonable degree of accuracy. You should be able to determine the consumption in 3000 to 6000 miles with much more confidence in the accuracy than you can get from working with this data. Whatever you are doing and whatever your engine is doing appears to be fairly consistent. That much can be inferred from looking at the data. But it looks to me that it is quite likely that your results could be consistently wrong.

You can't do it my way with that data. That's my point - GIGO (look it up if you don't know)

-jim

This Excel data does not even look like the same data as the PDF. For example, in your PDF file you have what is labeled a first reading at 321,771 miles and a second reading at 323,206 miles. That is an interval of 1435 miles. I don't see any interval in the Excel file that is even close to 1435. I see another 1st reading at 310,440 and a second reading at 311,635 which is an interval of 1195. But I see nothing in the excel file that corresponds with that number either. I'm sorry I don't know what to make of your data. I don't know if you have a lot of typos or arithmetic errors or if something else is going on.

I already told you the data is too spotty to actually know what the oil consumption might be to any reasonable degree of accuracy. You should be able to determine the consumption in 3000 to 6000 miles with much more confidence in the accuracy than you can get from working with this data. Whatever you are doing and whatever your engine is doing appears to be fairly consistent. That much can be inferred from looking at the data. But it looks to me that it is quite likely that your results could be consistently wrong.

You can't do it my way with that data. That's my point - GIGO (look it up if you don't know)

-jim

On 06/08/2010 06:59 AM, jim wrote:

so where is YOUR analysis, asshole? what - you don't have any? and you can't do the stats? and you don't actually have a damned thing to say other than whining loser bullshit? what a total non-surprise.

so where is YOUR analysis, asshole? what - you don't have any? and you can't do the stats? and you don't actually have a damned thing to say other than whining loser bullshit? what a total non-surprise.

--

nomina rutrum rutrum

nomina rutrum rutrum

jim beam wrote:

This would be a bad application for stats. I think the OP's study does an excellent job of illustrating why statistical analysis can be an exceptionally poor way to get a good answer. But what can you do - some people are so misguided they will attempt to use statistical analysis to tell them what day it is.

-jim

This would be a bad application for stats. I think the OP's study does an excellent job of illustrating why statistical analysis can be an exceptionally poor way to get a good answer. But what can you do - some people are so misguided they will attempt to use statistical analysis to tell them what day it is.

-jim

On 06/08/2010 08:04 AM, jim wrote:

yeah. said by the contribution-free asshole that doesn't have the balls to actually walk his talk.

yeah. said by the contribution-free asshole that doesn't have the balls to actually walk his talk.

--

nomina rutrum rutrum

nomina rutrum rutrum

Are you trying to champion stupidity?

I have been saying it is really dumb to use statistical analysis for determining something that is a basic accounting problem like determining oil consumption. And the only response you come up with is "why don't you show us the statistical analysis of oil consumption you have done". Are you saying If I can't match your stupidity - I shouldn't post?

jim beam wrote:

I apparently don't have what it takes to be as dumb as you that is for sure.

I have been saying it is really dumb to use statistical analysis for determining something that is a basic accounting problem like determining oil consumption. And the only response you come up with is "why don't you show us the statistical analysis of oil consumption you have done". Are you saying If I can't match your stupidity - I shouldn't post?

jim beam wrote:

I apparently don't have what it takes to be as dumb as you that is for sure.

jim beam wrote:

So let's see if i can follow this down the rabbit hole.... that would make you the one that can't read??? or..... are you the other one who sure is dumb???

So let's see if i can follow this down the rabbit hole.... that would make you the one that can't read??? or..... are you the other one who sure is dumb???

On 06/08/2010 10:21 AM, jim wrote:

wow, you just removed the question as to whether you're illiterate or deceitful - and you did it on your own!!! i wonder if you're dumb enough to not learn from that mistake??? [rhetorical]

wow, you just removed the question as to whether you're illiterate or deceitful - and you did it on your own!!! i wonder if you're dumb enough to not learn from that mistake??? [rhetorical]

--

nomina rutrum rutrum

nomina rutrum rutrum

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