Math Stat Which Is Correct

Is Statistics math?

I am quite surprised at some of the answers here, as I wold say only one of them to date, is correct with another pretty close.Statistics is considered by many universities as a separate subject, but they are linked through the definition of a probability space, which like all other spaces, is defied by an n-Tuple (Statistics having the 3-tuple defining a sample space, an event space and a probability function). For a formal intro, check out:Probability spaceSo yes, it's math, in the same way that Hilbert and Banach spaces are part of maths, but of course, focusing on Statistics.

ILATE or LIATE, which one is correct?

It's utter double Dutch to me but a quick search on Google brought up the following. I think the last paragraph answers your question.Integration by Parts - ILATE or LIATE?Which one is correct?The closer to the top, then the choice for u.(I) inverse trig functions(L) logarithmic functions (A) algebraic functions(T) trigonometric functions(E) exponential functionsor(L) logarithmic functions(L?) (inverse?) logarithmic functions(A) algebraic functions(T) trigonometric functions(E) exponential functionsFollow Math Help Forum on Facebook and Google+Read forum faster on mobile. Get the Free Tapatalk app?FREE - on Google PlayVIEWRegisterSave?RegisterHomeForumsAlgebraGeometryTrigonometryPre-CalculusStatisticsCalculusDifferential GeometryNumber TheoryDiscrete MathApplied MathDifferential EquationsBusiness MathPhysics HelpChemistry HelpAdvanced SearchForumUniversity Math Help ForumCalculusIntegration by Parts - ILATE or LIATE?Results 1 to 3 of 32ThanksThread: Integration by Parts - ILATE or LIATE?LinkBackThread ToolsDisplayOct 20th 2014, 08:16 PM#1Jason76 MHF ContributorJoinedOct 2012FromUSAPosts1,314Thanks21Integration by Parts - ILATE or LIATE?Which one is correct?The closer to the top, then the choice for u.(I) inverse trig functions(L) logarithmic functions(A) algebraic functions(T) trigonometric functions(E) exponential functionsor(L) logarithmic functions(L) logarithmic functions(A) algebraic functions(T) trigonometric functions(E) exponential functionsFollow Math Help Forum on Facebook and Google+Oct 20th 2014, 09:51 PM#2chiro MHF Contributor JoinedSep 2012FromAustraliaPosts6,591Thanks1712Re: Integration by Parts - ILATE or LIATE?Hey Jason76.You typically have a "feel" for the integral based on the substitutions used and there is no one single protocol that always works in all cases.With mathematics, if it gets you to the answer in a logical and mathematically consistent way then that is what matters.Thanks from topsquarkFollow Math Help Forum on Facebook and Google+Oct 21st 2014, 05:44 AM#3HallsofIvy MHF Contributor JoinedApr 2005Posts19,563Thanks2929Re: Integration by Parts - ILATE or LIATE?In other words, you should not try to memorize "rules" like that at all- instead, understand what it is that you are doing!Thanks from topsquarkFollow Math Help Forum on Facebook and Google+

Which is correct: "Math" or "Maths"?

To determine which is better, you have to show that one of the two has a weakness with respect to the other. This is the logical definition of the word “better.”So let us consider singularity vs plurality of the two abbrevation for mathematics.Mathematics is singular. There arent many mathematics there is only one. There are cetainly many braches of mathematics, but they are branchs.A tree has many braches, but we do not consider the word as plural. A tree, despite many braches, is singular.Likewise, mathematics has braches. Calulus is a branch; statistics is a branch; algebra is a branch and so on.Read definitions of words like algebra and you will often see something like: Algebra is a branch of mathematics having to do with …. Hence, mathematics is singular, just like the word tree.Now lets proceed to the next step.In English (east or west), short words that need to be made plural will be made to end in “s”.Branch to branches. Tree to trees. Cat to cats. Dogs to dogs.“Maths” connotes a plural form of math. But Mathematics is singular. They dont go together in terms of singulariy.In other words, math is in agreement with the singularity of mathematics.Let me go one step further. Brevity is a halmark of good style (See the book “The Elements of Style”)So the shortest abbreviation for a word is best.For example, consider another abbrevation for mathematics: mthmetics. It could be used to abbreviate ie to communucate the word mathematics. But its much longer than maths or math.Effective style is to use the shortest abbrevation that connotes the actual word.Math is shorter than maths. Math equally well connotes mathematics just as well as maths. But math is shorter than maths, making “math” better style.Therefore math is better with respect to plurality. Math is also better style.In short, there are obvious weaknesses in the word “maths” with respect to “math.”Hence, the better abbrevation for mathematics is math; not maths.

What are the correct answers to the following statistics questions?

For the first set of questions, C is wrong. This sample is in very likely to be biased, because people self-select them for the sample, for several reasons:You let people select themselves. And people with a higher interest pro or contra are more likely to react. So small but vocal groups will be overrepresented.You are only reaching the people who are watching television, at that specific time, on that specific channel. Very unlikely to be a nice reflection of the general (voting population)There is no check (or at least, it is not mentioned) to see whether people who call in, will actually be able to vote at all. (minors, people from different state/country)In the second set of questions, C seems wrong to me. I'd say that option a is correct, because:A is the definition of a random sample.B is certainly wrong (because it does not mention an equal chance)D is wrong because A is right and B is wrong.Which means to me option C has to be wrong as well, although intuitively it sounds right. I imagine that the phrasing allows for some trickery where chances of being selected depend on other units being selected or not. But that is just a hunch.In the last set of questions, i don't agree with B and C.In case of question B:Option A is incorrect: large response sizes are not that important, beyond a certain size it hardly matters. The way the sample has been established is way more important.Option B is incorrect: you have a large amount of non-response.Option C is incorrect: it has nothing to do with it.Option D is ergo also incorrect.In case of question C:Your sample are the letters you received, not the letters you've sent. To draw a parallel with the first set of questions: there you acknowledged that the sample consists only of the people actually responding. (phoning-in) Here actual response is mailing a reply.If we'd say - wrongly - that the sample is people receiving a letter, then the sample in the first set of questions would have been all people who were watching. (again, that would be wrong)

What is the major difference between statistics and math major students? As in primary goals/why statistics vs math.

There is a lot of overlap. I like to say that math is the logic of certainty, while statistics is the logic of uncertainty. For theoretical statistics, it's obviously important to have a strong math background, but math is also important for applied statistics. That's because it's crucial to be able to think logically, to be able to state and understand the assumptions behind methods, to be able to go back and forth between abstract and concrete notions, and to be proficient in probability, multivariable calculus, and linear algebra (especially matrix theory). There are interesting connections between statistics and almost every area of math.A statistics student should try to acquire strong math training, but should also seek out experience in working with and making sense of real data, in deciding when various assumptions are plausible in the real world, and in programming (I especially recommend R and Python).Many statisticians come from math backgrounds; this partly reflects how much math is needed in statistics, and partly reflects the fact that it's only a very recent trend for statistics to exist as an undergraduate major (in reasonable sizes). For example, I was a pure math major at Caltech, and it wasn't on my radar at all to do statistics (Caltech is a wonderful place, but does not have a Statistics Department or many courses or research in statistics). One thing I loved about math then (and still do) is the connections with physics, biology, economics, and so many other fields. Mathematical thinking helps you to see the essential pattern/structure of a problem, and this is crucial for statistics too.At the graduate level, there is a tendency for math to become more and more abstract and disconnected from the rest of science, so I was very happy to discover that statistics let me regain this, and have the best of both worlds: you can apply statistical thinking and tools to almost anything, and there are so many opportunities to do things that are both beautiful and useful!

Is Probability theory correct?

Most mathematical theories are proven right or wrong without any reference to empirical data. For example, if it were found that there were exceptions to Fermat’s Last Theorem or the prime number theory, that wouldn’t mean you should refine the theory based on empirical (physical) data; instead it means that when mathematicians accepted the proof, they made a goof and let through some logical error.But probability theory is in a very strange category. The laws of probability, in general, and statitistics in particular, can be used to make predictions about outcomes in the physical world. And what people who employ statistics have found is that, in general, the results suggest they should have a high degree of confidence in their work — provided they have done the work correctly AND provided that they haven’t been misled by failing to account for hidden correlations……which of course happen all the time. :)But of course, that’s the rub. Look at it this way. Suppose I have a six-sided die and I tell you absolutely nothing about it except 1) there are six sides and 2) when rolled, exactly ONE side coes up, no more, no less.Now you make your predications — about each number coming up approx. 1/6 of the time — and roll the die. Out of the six numbers (1, 2, 3, 4, 5, 6), you roll a thousand 3’s in a row. What does that mean????It could be taken as good evidence that the die is not fair, that it is heavily weighted in favor of 3’s. Even though I all have is empirical evidence.But it could also be that the die IS fair, that all the 3’s came up by pure chance. Any mathematician will tell you that it is in face entirely possible for a MILLION 3’s to appear in a row, BY PURE CHANCE ALONE, but that doesn’t change the mathematics.Statistics, therefore, tends to live in a very strange Twilight Zone between pure mathematics (which can never be wrong if done correctly), experimental science (in which empirical results are grounds for revising a theory), and wishful thinking. (Maybe the dice aren’t loaded against me; maybe I just had bad luck in Vegas… or DID I?)Probability theory and statitics, at some point, almost intersect with philosophy. Or even religion…. if you think that praying hard enough will affect the outcome of the dice!