505:), as well as to upper-level undergraduate and graduate physics courses taught from the same perspective. (Note that as a math major in college I took 3 semesters of physics alongside physics majors, but none of what I learned was what I'd call "mathematical physics"!) Similarly, just because most statistics being used nowadays is mathematical in nature and follows the mathematical work of Legendre, Galton, Pearson, etc., doesn't make it all "mathematical statistics". Instead, that term is used mainly in academia to refer to research and undergrad/grad courses based on techniques of (mostly) mathematical analysis. There is a contrast to be made with physics, however, in that I think I would count a lot of calculus-based introductory statistics classes as (elementary) mathematical statistics, whereas I don't think most calculus-based introductory physics classes count as mathematical physics. (But perhaps that could be attributed to my own bias or ignorance.)
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Some elements of statistical reasoning demand a higher level of ability and/or training in maths than most people can cope with or been educated in, and this disparate set of techniques can conveniently be called 'mathematical statistics'. If you wish, I can list the topics that the Open
University consider to be mathematical statistics. There is absolutely no assertion on my part that the rest of stats is 'non-mathematical'. If you like, we could effectively split stats into 'easy stats' and 'Less easy stats' with mathematical stats being the latter. @MaxEnt yes, non-academic statisticians would draw approximately the same line- for instance, none of the stats used by Six Sigma practitioners industrially would be mathematical statistics.
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beaves in the classical way. The particles are very small, extremly many, observed and in normal life the conditions are always fulfilled. It is not until the individual particles are studied they behave like
Quantum mechanics. If these very specific mathematical coincidences wouldn’t exist we would most likely see our world as a thick soup. And if the conditions would not be fulfilled we would see our world very fuzzy and with no answers, black, blind. Because it is a set of very specific mathematical coincidences the sharpness decreases extremely rapidly when the condition fulfilment is slightly worsen. This is why a statistical report with 30% non-answers is pure scientifically trash.
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idealized null hypothesis of no relationship between two data sets. Rejecting or disproving the null hypothesis is done using statistical tests that quantify the sense in which the null can be proven false, given the data that are used in the test. Working from a null hypothesis, two basic forms of error are recognized: Type I errors (null hypothesis is falsely rejected giving a "false positive") and Type II errors (null hypothesis fails to be rejected and an actual difference between populations is missed giving a "false negative"). Multiple problems have come to be associated with this framework: ranging from obtaining a sufficient sample size to specifying an adequate null hypothesis
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across a region, not the upwards axis itself. The dashed lines supposedly indicating 1, 2, and 3 standard deviations are clearly wrongly placed. The two points of inflection on the true normal gaussian curve are by definition at ±1*sigma, so even visually it is easy to tell those lines are not correct. In line with the last point, the lines indicating 95% and 99% density very clearly do not cover intervals corresponding to 95% and 99% of the area under that bell curve. There is also an x-bar symbol above the density plot, which is not really appropriate as sample variance is only normally distributed with a known population variance, which is almost never the case.
191:. Sorry guys, the above reasons for support won't wash. It's obvious, innit, that statistics is a subset of mathematics. However, there are particular areas & methods within statistics that rely more directly on mathematical techniques than others, and these areas can be grouped and called 'mathematical statistics'. Look, for example, at the modules available from the Open University: among a number of statistical modules there is a level 3 one called 'mathematical statistics'. So don't deny that there is such a field within statistics, and don't claim that is the whole field. People using statistics recognise the validity of the description.
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growth and welfare positively answered gladly any questions. However the telecom network structures are fragmented, the mobile phone world is harder to get a correct sample from and people are reluctant to answer, having no identification of the answering benefiting their life anymore. In fact getting the non-answers below 10% is today almost impossible today, in short the results are often nothing but trash. The problem for many customers of statistics today, is that they are not aware enough to judge the quality of the surveys they are buying. They want it badly and often don't want to know the backside.
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other analytical process just because it is (in your opinion) more difficult to apply on paper. If that is the case then I must say you haven't understood at all what mathematics is about (and it is probably why concepts that are common knowledge to a mathematician are "numpty" to you). The fact is that any trained statistician or specialised mathematician knows that the principles of statistical inference are pure mathematics in nature and have been established by means of mathematical proof, something which cannot be said for, e.g., the algorithmic inference made by predictive models in
493:. A lot of physics requires mathematical calculations, of course. And almost all of the physics in use nowadays (being learned by students and being applied by scientists and engineers) was developed after — and is in some way a direct result of — Newton's application of then-cutting-edge mathematics to the subject. But that doesn't mean all of "today's physics" can rightly be called "mathematical physics". Instead, the term (as I understand it) refers to current research in physics that employs various techniques from
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sampling variation). Descriptive statistics are most often concerned with two sets of properties of a distribution (sample or population): central tendency (or location) seeks to characterize the distribution's central or typical value, while dispersion (or variability) characterizes the extent to which members of the distribution depart from its center and each other. Inferences on mathematical statistics are made under the framework of probability theory, which deals with the analysis of random phenomena.
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statistics every day without being aware. But when the sample in ordinary human life experiences is not random they can get indeed very prejudiced. Like watching a town square and estimate the share of immigrants in the country will give the wrong impact, because immigrants have less good housing and tend to be not at home more than domestics. In short the sample is biased, non-random. But we unaware use the sample methods getting our minds. Being aware makes us realise misjudgements.
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226:. If there was no more to statistics than mathematical statistics, the 'mathematical' prefix would be redundant. But there is much more, such as the non-mathematical aspects of the design of surveys, experiments and observational studies, graphical and tabular display of data and results, the philosophy of statistics, plus the whole body of knowledge about how to chose which mathematical method to use.
243:. "Statistics" as a scientific field is synonymous to "mathematical statistics", which should be distinct from the everyday use of "statistics" that refers to "summary statistics". The "Statistics" article should be either redirected to mathematical statistics or become a disambiguation page for "mathematical statistics" and "summary statistics".
209:,then confusion reigning is understandable. It starts off with some very wobbly defintions, and proceeds to fill much of the article with stuff which I would call stats, not mathematical stats. Please suspend the "merge" request for a month and I'll try to change the math stat article so that at least it does what it says on the tin.
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The need for data and the money in the business makes always suppliers when jobs are offered for good money. Especially the news media and politicians are heavily dependent on surveys of political faith. The commercial marketing is also in very strong need and with good economic resources. As long as
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The other way, if we start to study the answers of the individuals in a sample, it says nothing but the individual. And the individual can behave any way. It will get crazy pictures, might not be
Quantum mechanics but still quite crazy. Individuals and populations are indeed not the same and can’t be
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The Sample statistics is possible because of a few very specific mathematical conditions/coincidences and is dependent on that the conditions must be completely fulfilled to be able to use this beautiful luck of the mathematical coincidences. Else the sample is not a sample but a very tiny population
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I'm not sure what you mean by "user making simple arithmetic on the normal distribution" but this sounds like a very personal point of view based on a very personal perception of statistics and mathematics in general. You seem to imply that differentiation is allegedly closer to mathematics than some
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In the 1970ies and 1980ies telephone interviews were very efficient means in countries like Sweden where all had fixed phone lines of the governmental monopoly telecom operator. The operator could sell phone lists to the statistical operators for use. People being used to the good society with rapid
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In general making larger samples than 1000 have very little effect on the accuracy, it is a consequence of the nature of the mathematical conditions/coincidences. Reading about larger samples always put the question, if the manager of the survey really knows the statistics skill? The reason is large
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Analyse of the non-answers must not reveal a tendency (like all non-answers are communists or religious, non-answer often of a philosophical reason), even if all other conditions are fulfilled, if it fails here, the result is scientific trash. There are no ways of repairing a failure of the previous
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I recommend being somewhat conservative with the "lead image". Something simple and recognizable to someone who knows a little statistics (hence my preference for a normal distribution), and yet visually interesting enough to attract the interest someone who doesn't. Note that, as of a few days ago,
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Claiming that statistics is not a branch of mathematics is like claiming that energy is unrelated to mass. Clearly the basis of statistics is mathematical logic and mathematical operators. It is doubtful that
Pearson, Gauss, or any other progenitor of statistics would claim that it is independent of
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On the other side, does non-mathematical statistics even make sense? Imagine telling some math-hating child "oh, this isn't math, it's least squares". Statistics prior to least squares has about the relation to modern statistics that alchemy has to modern chemistry (defined error estimator about as
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A standard statistical procedure involves the test of the relationship between two statistical data sets, or a data set and synthetic data drawn from an idealized model. A hypothesis is proposed for the statistical relationship between the two data sets, and this is compared as an alternative to an
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Simplified it can be expressed like, the world behaves in the classical way humans expect it, as long as we fulfil the basic Sample statistics conditions. It means that if we are watching at least 1000 physical particles (that
Quantum mechanics manages) and 950 of them are observed, them as a group
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Perhaps a way of moving forward on this is for one user to take it upon themselves to implement one solution (i.e., in their userspace, with the help of other interested parties) and another user to implement the other solution, and then it will come down to a more concete descision: which solution
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For my own purposes, I might be tempted to lasso traditional statistics (distilled facts about national populations useful to government) under a page titled "statistics (public administration)". But I'm sure not going to invent an arbitrary wall to partition statistics into "statistics (alchemy)"
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the difference." Unfortunately, the standard isn't "understand", it's explicate. Would any two of these intuitive non-specialists draw essentially the same line? If not, what we have here is a noddable of nonagreement, where everyone agrees internally that such a line exists, but when pressed no
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Response. Let me try one more time. The sub-field of mathematics, which is statistics, is useful to a great number of people, of a very wide range of ability, training, and experience. Many elements of statistical thinking and reasoning are sufficently easy to use that lots of people use them.
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is perhaps not a useful one for our purposes. Therefore, if we're going to merge and redirect one of them to this article, I would say merge and redirect both; and if we're going to keep them separate from this article, then I would say merge and redirect one to the other. (Note, BTW, that both ST
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Looking through these, it would seem that "Mathematical X" ("MX") is typically described as involving the application of mathematical methods to the field X, whereas "Theoretical X" or "X theory" ("TX") is more concerned with providing theoretical explanations of observed phenomena in the field X.
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In other words the basic Sample statistics conditions have a huge impact in ordinary daily life of humans. This is also processed by the human mind in the form of experience and expectations. When seen a 1000 times most people have a pretty strong feeling for what could be expected. We use Sample
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The first picture posted on this page as representative of statistics is extremely flawed. The upwards axis posted next to the graph should not be labeled as probability, but probability density, because the normal is a continuous distribution and a probability on that distribution is an integral
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Statistics is confusing enough as it is. Perhaps we shouldn't complicate it any further than it needs to be. I'm not trying to be rude, so I hope this is taken as a friendly piece of criticism. At the very least, though, citations should be used accurately. Perhaps the definition you used was
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for processing data is that the result of data collection is often represented by something looking like a swarm of dots on a two dimensional data chart. To be able to use the data it has to be converted to a mathematical trend line and for that statistical mathematical equations are used. These
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entirely -- personally i'd like one that includes some real data with some form of statistical fit. After a quick browse around
Commons I quite like this one as it's of considerable historical importance yet reasonably clear and visually appealing at a limited size, and it shows real data plus a
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Comment: the statement ' "Statistics" as a scientific field is synonymous to "mathematical statistics", ' is a numpty statement. Let's take two examples: 1. Much work with the normal distribution involves the user in nothing more than simple arithmetic, and so is not considered to be part of
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Two main statistical methods are used in data analysis: descriptive statistics, which summarize data from a sample using indexes such as the mean or standard deviation, and inferential statistics, which draw conclusions from data that are subject to random variation (e.g., observational errors,
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First: I don't have a problem with using a normal distribution picture to represent statistics. I mean, no picture is going to represent everything, and the normal distribution is as good as anything else. But you are quite right that this particular picture of the normal distribution is wildly
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The preceding comment (by Not-a-parted-haired-libertarian) was moved from the next section to this one, because I think the editor simply made a mistake when they placed it at the bottom of the page. I added the "Support" label for the convenience of readers. Note that this user has since been
520:. With this in mind, it is perhaps instructive to consider other fields of study X that not only have an article or redirect at "Mathematical X" but also at "Theoretical X" or "X theory". These include (omitting variations that use "theory" in a different sense than the one under discussion):
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While the math can be processed in ordinary common computers, getting the data especially in Sample statistics can be very tricky and very expensive. In most surveys minimizing the non-answers (is very essential for the usability of the result), cost more than the rest of the entire survey.
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I've probably read the definition of "statistics" once or twice before, but I've never seen it specifically (yet so vaguely) attributed to "people in a state." So, I decided to pay
Merriam-Webster.com a visit (the source cited) and this is what it actually has listed for the definition of
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In Full population statistics there are problems with data collection mainly dependent on the accuracy of the data in governmental administrative systems. The main issue is if the collected data is really what it is expected to be and that is dependent on how the data is produced in the
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The next issue is: I think that the picture is intentionally "schematic" and not to-scale. If you make the picture realistically scaled, then are the horizontal lines for "95%" and "99%" too close to be visually distinguished? If so, then let's replace them with the 68% and 95% lines at
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for processing data of a specific kind, from a defined population, to get scientific describing results. With the statistics come some sub-activities dependent on the demands of the statistical methods like; data collection, organization, analysis, interpretation and presentation.
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involves the frequent use of differentiation, and so is considered mathematical statistics. The inability of pure mathematicians and non-mathematicians to recognise the difference is frankly, irrelevant. Ask a non-academic statistician and s/he will understand the difference.
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true at the time of writing, although I find it hard to believe
Merriam Webster would use such a definition for statistics. Stranger things have happened I suppose. Either way, I just thought I should let you know. Emerald Evergreen 18:14, 27 January 2017 (UTC)
1401:. Mainly because the non-answers are far too many. It is a mathematical coincidence with tight conditions, making something very cheap and usable possible, but only if the conditions are meet. This is why in politics predictions seems to be less good these days.
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and says nothing about the intended huge population. In short the result would be scientific trash. However fulfilling the mathematical conditions/coincidences the sample can be projected on an as huge population as ever, millions and billions of individuals.
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Sample statistics are commonly used by the authorities in planning the future society but one of the major users is private marketing getting the data about customer’s preferences. It is a relatively cheap way of getting very good quality information.
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It seems disingenuous to represent all of statistics with this particular picture given its inaccuracies. I could render a replacement in R in a few minutes, but I wanted to post to the talk page before apparently arbitrarily replacing the main image.
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Full population statistics are made by governments and authorities most of the time based on data from governmental administrative systems and is a side effect of administrating a country, town or other units. It is normally referred to as
National
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As for the 95%/99% vs. 68%/95% issue, I would try to keep 95%/99% in there, if possible, since those are common confidence levels (for example), and no one cares what precise range actually contains 68% of the probability (as they do with 95%). -
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until a consensus is reached, and anyone is welcome to contribute to the discussion. The nomination will explain the policies and guidelines which are of concern. The discussion focuses on high-quality evidence and our policies and guidelines.
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Statistics is also treated as separate to mathematics in scientific literature. For example in arvix it is not considered a branch of mathematics. In the world of scientific journal's math and statistics tend to be treated separately.
1007:, a different (older) version also purportedly by Galton, although that one seems a bit too "technical" for a topmost image. Personally, I think a normal distribution image is ideal, if we can get one that's clear and correct. -
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Now, despite the fact that many people call statistics a science, there isn't really the same level of interplay between theory and experimental observation as in the other sciences listed above. So any distinction between
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474:(or elsewhere… more on that in a moment). OTOH, many objections to having MS as a separate article seem to be based on a misunderstanding (or mischaracterization) of what the word "mathematical" implies about the topic.
1321:. This makes gold always looks like gold and water like water, there are no Quantum mechanics surprises in the common human world. In a group of many the particles as a group statically behaves always as expected.
344:, another page name for old-school statistics would apparently be "statistics (unenlightened)", and then I guess old-old-school statistics would be "statistics (applied phlebotium)" — look ma, no math at all! —
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that just happen to be inspired by the field X (i.e., to find mathematical truths), whereas "TX" exists to find better explanations of observations collected in field X (i.e., to find scientific "truths" ).
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It would be better to say "statistics is a science" than "statistics is a branch of mathematics", since the later takes sides in an on-going dispute (you can for example see this dispute on CrossValidated
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The x-bar symbol above the y-axis seems to be marking the mean of the distribution, not claiming that this is the distribution of the sample mean. Accordingly, it should be marked with the symbol
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Merriam-Webster dictionary defines statistics as "classified facts representing the conditions of a people in a state – especially the facts that can be stated in numbers or any other tabular or
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Or perhaps something like this if we want to illustrate that statistics has moved on a bit since simple linear regression? Opinion polls are a use of statistics that's familiar to most people.
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of interest to mathematicians, whereas "TX" tends to be a subfield of X. One might take the contrast to the extreme and say that "MX" investigates the properties of, and relationships between,
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Users may edit the page during the discussion, including to improve the page to address concerns raised in the discussion. However, do not remove the deletion notice from the top of the page.
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The practice or science of collecting and analysing numerical data in large quantities, especially for the purpose of inferring proportions in a whole from those in a representative sample.
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dependent on a few very specific mathematical conditions/coincidences allowing the results of a small sample group of a huge population to represent/be projected on all the population
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Statistics being a branch of mathematics, depends on your definition of mathematics. I'd argue that certain aspects of statistics are outside the scope of mathematics, like:
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The article is today like a general conversation about statistics, but does not give the reader a clear picture of the question, what is statistics. The article about
324:. Generally I prefer splitting over lumping, but the cuts need to be helpful, rather than obstructive. Gravuritas says "Ask a non-academic statistician and s/he will
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1083:, while deadly dull, is at least correct looking. How 'bout that as an interim choice, until a better option can be found? Alternatively, since you like real data,
1431:. Please continue your interest in helping Knowledge, in accordance with its policies and with due respect for the consensuses and compromises that already exist.
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Good spot about the problems with the image. Without checking, I suspect it's been there an awfully long time. I think it's time to reconsider the lead image for
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As history goes on, scientific disciplines get more specialized. It is doubtful that Newton would regard physics and math as distinct disciplines, but now we do.
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fitted line. Linear regression is familiar to many so not too scary, but on the other hand it could seem old-fashioned and dull... Comments? Better suggestions?
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blocked for sock puppetry (not, AFAIK, involving any other user who has commented here) and disruptive editing, but this comment seems reasonable, so… -
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is only normally distributed with a known population variance" , which is not actually true, as the distrubtion of the sample mean does not depend on
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One of the most interesting aspects of Sample statistics is that its very specific mathematical conditions/coincidences are the connection between
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As per rationale via
Knowledge:Articles for deletion/Mathematical statistics (2nd nomination). Appears to be the third suggestion to merge.
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all logged-out users are (by default) now seeing the image we're talking about when they hover on links to this article (log out or change
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seems better. (Although keep in mind that some interested parties might not be able to devote much time to this until the summer…) -
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might make the population to fool the administrative system and so the statistics. Another common problem is public opinion and
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Support for political parties in New Zealand in 2005–2008, according to various political polls. Fitted smooth curves are from
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1: a branch of mathematics dealing with the collection, analysis, interpretation, and presentation of masses of numerical data
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Subsequent comments should be made on the appropriate discussion page. No further edits should be made to this discussion.
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Subsequent comments should be made on the appropriate discussion page. No further edits should be made to this discussion.
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I take issue with the following that was written in this Knowledge article (introduction section, fourth line from top):
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Full populations (all Londoners, all German men over 2m tall etc), including data from every individual of the whole
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is very fuzzy too. A question is also how the statistical topics in the Knowledge should be organised, sub-divide?
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back in August 2004, when there was very little statistical information in Knowledge.) This has come up repeatedly
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Needs a section on applied statistics in medicine and credit to Florence Nightingale for pioneering this field.
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and MS are linked to by a similar number of other articles. By my count, not counting template transclusions:
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These are very different topics, and the combined article would be too varied to be useful to many people.
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or just the word "mean" instead of x-bar. (Note, BTW, that the OP presumably wanted to say "sample
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There is a lot of statistics that is outside the scope of mathematics, you can see my examples in
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928:, whether known or not. But that's kind of beside the point in the present discussion.) Oh, and "
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We should combine the articles because the articles are so similar and basically are the same.
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There needs to be more information on statistical modelling as well as Bayesian statistics.
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and "statistics (chemistry)", as if that usefully aids the great unwashed who visit here.
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is not actually very mathematical, though it certainly discusses mathematical concepts.
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there are someone willing to pay for the impossible there are always people offering
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1079:. I wish I could just edit the SVG to correct the mistakes, but I can't (currently).
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which you have to support your proposed changes, the article should stay as it is.
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There must be a sample of at least 1000 individuals to answer specific questions (
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mathematics and such assertions are self-important at best and ludicrous at worst.
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to check this). So, it's time to make a change, I think. I don't really like
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certain principles that relate to real-world data (for example the
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https://stats.stackexchange.com/questions/78579/stats-is-not-maths
438:, not the other way around. Also, I should point out upfront that
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I think this Statistics article should start something like this:
1423:. And there you were told that Knowledge editors need to avoid
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Statistic methods are used in general in two specific cases:
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Addressing the second point first: The distinction between
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and a lot of statistical reports we see today are in fact
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The book on non-mathematical statistics must be very thin.
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samples are very expensive and delivers almost nothing.
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https://en.oxforddictionaries.com/definition/statistics
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At least 90% must answer, preferably 95% should answer
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is suitable for inclusion in Knowledge according to
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explained it this way (paraphrasing remarks made at
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Knowledge:Miscellany for deletion/Portal:Statistics
430:. (First off, please note that the proposal is for
977:'s 1889 graph of offspring height by parent height
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1290:of the full population the sample is representing
458:. Most of the arguments I've seen that MS should
1365:Data collection is often the most expensive part
342:Darwin, Galton and the Statistical Enlightenment
329:two people wish to carve it in the same place.
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592:The distinction is a subtle one, but IP editor
1349:methods also give quality measurements of the
750:I much prefere oxford dictionary's definition
358:Talk:Statistics#Definition_of_.22statistics.22
1275:The basic Sample statistics conditions are:
440:I created the Mathematical statistics article
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936:. But that's just my personal preference. -
784:rather than a field of study and research.
258:mathematical,statistics. 2. Some work with
1482:A discussion is taking place as to whether
174:. Statistics is a mathematical discipline.
1370:administrative systems. Side effects like
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1286:The sample must be selected by absolute
924:of the population variance, only on its
870:inaccurate. Thanks for pointing it out.
792:2600:1012:B059:C76A:6C05:6933:637E:DC6A
516:that points not to that article but to
1337:Statistical methods of processing data
508:In any case, note that we also have a
44:Do not edit the contents of this page.
462:be merged here seem to be based on a
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1447:Concur with Mgnbar. If there are no
1077:commons:Category:Normal distribution
686:2: a collection of quantitative data
628:365 links to Mathematical statistics
554:Mathematical and theoretical biology
115:The following discussion is closed.
1490:Knowledge's policies and guidelines
1376:General Data Protection Regulation
1111:Template:Statistics topics sidebar
512:article, as well as a redirect at
24:
1419:You have made similar remarks at
485:is quite similar to that between
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1034:with the grey bands showing 95%
648:The discussion above is closed.
600:): "MX" tends to be a branch of
29:
1069:your "Page previews" preference
624:449 links to Statistical theory
468:that has never actually existed
396:Not-a-parted-haired-libertarian
1499:The page will be discussed at
1259:to make working town bodies.
970:File:Galton-height-regress.jpg
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1427:and support their edits with
1194:I Think this article is fuzzy
1189:18:21, 12 February 2019 (UTC)
1169:14:12, 5 September 2018 (UTC)
832:21:22, 25 December 2017 (UTC)
817:14:04, 25 December 2017 (UTC)
665:Some popular definitions are:
293:10:04, 21 December 2016 (UTC)
273:01:17, 17 December 2016 (UTC)
253:22:35, 16 December 2016 (UTC)
236:17:49, 15 December 2016 (UTC)
219:17:14, 15 December 2016 (UTC)
205:PS having just looked at the
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142:16:10, 29 November 2016 (UTC)
1153:STATISTIC A FILE OF FORMAT
349:18:31, 11 January 2017 (UTC)
1514:13:23, 1 October 2019 (UTC)
1425:Knowledge:Original research
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153:Remarkably, the article on
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1429:Knowledge:Reliable sources
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892:17:40, 11 April 2018 (UTC)
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657:Definition of "statistics"
644:17:51, 23 April 2017 (UTC)
421:10:02, 23 April 2017 (UTC)
404:14:28, 10 April 2017 (UTC)
1461:02:11, 10 June 2019 (UTC)
1441:01:29, 10 June 2019 (UTC)
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1378:limiting available data.
776:13:59, 4 April 2017 (UTC)
732:14:05, 4 April 2017 (UTC)
387:17:39, 4 April 2017 (UTC)
370:14:38, 4 April 2017 (UTC)
314:17:33, 5 April 2017 (UTC)
108:05:45, 27 July 2017 (UTC)
1492:or whether it should be
1315:Probability distribution
1175:Note on future expansion
712:statistical algorithms
680:Definition of statistics
671:classified arrangement".
650:Please do not modify it.
598:Talk:Theoretical physics
117:Please do not modify it.
619:mathematical statistics
582:Mathematical psychology
518:Mathematical statistics
483:mathematical statistics
432:Mathematical statistics
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499:mathematical analysis
42:of past discussions.
1109:Hey, I just noticed
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909:{\displaystyle \mu }
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701:Likelihood principle
606:mathematical objects
542:Mathematical biology
491:mathematical physics
260:Likelihood functions
88:Proposed merge with
1239:Sample (statistics)
1200:Sample (statistics)
602:applied mathematics
546:Theoretical biology
495:applied mathematics
456:(4 different links)
340:After checking out
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510:Statistical theory
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1311:Classical physics
1307:Quantum mechanics
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1372:Tax evasion
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934:Student's t
594:5.151.82.74
466:MS article
36:This is an
1396:scientific
1343:mathematic
1288:Randomness
1253:Demography
1214:mathematic
1135:incomplete
1003:Note also
984:Statistics
768:Mcshuffles
720:Mcshuffles
578:Psychology
479:statistics
472:Statistics
436:Statistics
362:Mcshuffles
326:understand
306:Gravuritas
265:Gravuritas
211:Gravuritas
193:Gravuritas
922:knowledge
782:statistic
560:Economics
525:Chemistry
379:Elliot321
137:Nightfury
79:Archive 5
73:Archive 4
68:Archive 3
60:Archive 1
1453:Rollidan
1309:and the
1157:unsigned
851:unsigned
788:unsigned
728:contribs
716:unsigned
1494:deleted
1406:Zzalpha
1329:ever.
930:T-score
538:Biology
487:physics
392:Support
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147:Support
39:archive
1433:Mgnbar
1399:humbug
884:Mgnbar
824:Mgnbar
709:biases
453:decade
375:Oppose
354:Oppose
346:MaxEnt
285:Delafé
245:Delafé
224:Oppose
189:Oppose
176:Jmc200
129:Nordic
1392:fraud
1115:dcljr
1097:dcljr
1095:). -
1009:dcljr
953:dcljr
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926:value
878:and 2
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16:<
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626:and
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481:and
450:past
444:over
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1353:.
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766:---
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