Can somebody tell me how to understand Statistics?
458174
Actually, statistics books are notorious for being written in such a way that no normal human can understand them. The trick, generally, is trying to find a way to relate the problems to something you're interested in. For example, if you like basketball: one possible sampling distribution would be the number of free throws individual players make over a season. You could take a sample of, say, 10 of the players and find the mean and standard deviation. You could compute a 95% confidence interval with that information, which would allow you to say that you're 95% confident that the average number of free throws made by NBA players in a season will be between this number and that number. You could find the probability that a given player would make at least a certain number of free throws in a season by finding the z-score and looking it up on the normal probability distribution table, etc. If you're really struggling with the terminology, I recommend visiting your math help center on campus (most of them have one), or contacting a tutor.
704942
Range is the highest minus the lowest number of your data (in the above example, 15 -1 = 14 would be the range)\nThe mean is the average of all your data\nTo find the median yo have to order all the numbers and the central one is the median, for example, 1 4 5 6 6 7 8 9 11 12 15\n7 is the median because is in the middle.\nThe mode is the one that repeats the most in the serie, in the same example 6 would be the mode...\nThere are some formulas for more complex set of data, if you need them let me know..
29267
Statistics started out as a study of chance and the odds of games. \n\nThe original use for statistics was in predicting chance events. Jacques Bernoulli (1654-1705) wrote "The Art of Conjecture" which is the art of evaluating as exactly as possible the probabilities of things. \n\nGerolamo Cardana (1501-1576) Wrote the first book on probability, 'Liber de Ludo Aleae' which is about games of chance.\n\nRene Descartes (1596-1650) Believed that the universe had a mathematical structure. Much of his philosophy lies in that base. Although his stuff is more towards algebra than statsistics per se.\n\nRonald Fisher (1890-1962) In 1922 he gave a new definition of statistics. Its purpose was the reduction of data and he identified three fundamental problems.
351084
Most times statistics are used in psychology to measure whether the results of an experiment shows genuinely "significant" differences within the results, or whether all of the results fit within a single range.\n\nFor example, there have been studies which "appear" to show that boys' and girls' academic performance goes in non-synchronous waves.\n\nIf you measured the performance of all the pupils in a school in a certain year in a certain subject you could tell (using chi square, for example) whether the performance of the boys (as a group) was statistically different from the performance of the girls (as a group), or whether the performance of all the students in that year, in that subject, fell within the same "range".\n\nIf there is a significant difference you can use "standard deviations" as a measure of just how big the difference is.\n\n(I don't have any URLs on hand, but you can look up "statistical significance" and "standard deviations" online.)
615933
Teaching graduate students the proper ways to analyze data statistically is one of the most difficult things- It isnt interesting to them, it's hard to grasp, and there are rules for variance, independent and dependent variables, sample populations and distribution, even and uneven sampling comparisons..on and on.
774817
I can tell that nobody wants to just do this problem.  There's nothing interesting about it.  It's a typical problem that a stat student does to show understanding.  Get out your textbook and study up how to solve it.
291590
There are several good statistics textbooks free online, and free software, too.  Be sure to check out R, the free statistics software package.
98588
The difficulty level of Introductory Statistics, like any class, really depends on your professor.  Is he/she going to allow you use of a good calculator (one that can find standard deviations, factorials, etc.) or an equation sheet?  There are a lot of equations and distributions to remember, so it may be hard if you aren't allowed to use an equation sheet.  Some professors may teach the class based on a computer program, for example DDXL or Excel.  Some professors may opt for a project based final (easier than a test in my opinion) or may require you to sit a final exam.  \n\n"Hardness" is relative...suggestions would be to go to class, make sure you understand the distributions and concepts (permutations and combinations is fairly difficult but not generally a major part of the class) and do your homework.  If you need help with a few problems there's always Yahoo answers...I'll be glad to help!  :-)
1161921
A really good book is Bayesian Data Analysis, Second Edition, by Andrew Gelman, et al.  I found it to be one of the easier to comprehend books on Bayesian statistics.  It was as "rigorous" as you might like, but I have found it absolutely useful in day to day analysis tasks.\n\nHowever, I have to admit that until I had a formal course in Bayesian Statistics, reading all the books I tried to read on the subject just didn't get to the fundamental gist.  David Draper out of the University of California, Santa Cruz is about one of the best mathematics / statistics lecturers I've ever encountered.  He put together the foundation that helped me understand the Gelman work.  But reading Gelman first helped me appreciate what I was learning from Draper.  If Draper ever finishes his book (the basis for the course notes), I'd recommend that as a good foundation for more rigorous understanding.
824818
OK, here goes:\n\nThe data could be\n7 9 10 12 12 13 14\n\nThe median (center number) is 12\nThe mode (most repeated number) is 12\nThe mean (average) is 11.\n\nThe point is that you need to look at all three measures to get a good idea of the data.\n\nHere's another set:\n1 3 10 12 12 19 20\nThis has the same measurements.\n\nIt is only when we look at things like the variance and std deviation that we can really see the difference between those two data sets.\n\nGood luck!
246517
(m)\n\nBusiness statistics is the science of good decision making in the face of uncertainty and is used in many disciplines such as financial analysis, econometrics, auditing, production and operations including services improvement, and marketing research. These sources feature regular repetitive publication of series of data. This makes the topic of time series especially important for business statistics. It is also a branch of applied statistics working mostly on data collected as a by-product of doing business or by government agencies. It provides knowledge and skills to interpret and use statistical techniques in a variety of business applications. A typical business statistics course is intended for business majors, and covers statistical study, descriptive statistics (collection, description, analysis, and summary of data), probability, and the binomial and normal distributions, test of hypotheses and confidence intervals, linear regression, and correlation.
571247
i wish i could help you...it looks like you need a stats book...i was tryin to find this website i used to use in my stats class...but of course when you are lookin for somethin u cant find it...sorry about that
837986
http://www.statsoft.com/textbook/stathome.html
124967
Probability:\nA measure of how likely it is that some event will occur\n\nstatistics:\nA branch of applied mathematics concerned with the collection and interpretation of quantitative data. \n\nProbability theory is one of the tools that is used in statistics.\n\nhttp://www.futureaccountant.com/probability/\nhttp://www.schoolingkids.com/
242094
In the experiment of testing for the number of students out of 37 who consider statistics exciting\n\nNo. of trials made \n==> No. of students tested = 37\n==>n = 37\n\nLet the event of a student tested being intersted in the subject of statistics be a success\n\nProbability of success in each trial\n= probability that a student tested is interested in the subject of statistics\n==> p = 0.75\n[Given that 75% of the population of all business statistics 1 students consider statistics exciting]\n\nTherefore, \nq = 1 - p ==> q = 1 - 0.75 ==> q = 0.25\n\nLet "x" indicate the number of successes in "n" trials\nsince the number of students who are interested in statistics can be either 0, 1, 2, .... 37\nThe values "x" can carry are 0, 1, 2, .... 37\n==> "X" is a discrete random variate with range = {0, 1, 2, .... 37}\n\nThe probability distribution of "x" is a binomial distribution..\n\n[Since there a number of trials all of which are identical and independent with only two possible outcomes in each trial either a success i.e. the student being interested or a failure i.e. the student not being interested, with the probability of success in each trial remaining the same all throught]\n\nThe probability function of a binomial distribution\n==> P(X=x) = nCx * p^x * q^(n-x)\n\nTherefore, for the above distribution\nP(X=x) = 37Cx * (0.75)^x * (0.25)^(37-x)\n==>P(X=x) = 37Cx * (0.75)^x * (0.25)^(37) * (0.25)^(-x)\n==>P(X=x) = 37Cx * (0.75)^x * (0.25)^(37) * 1/(0.25)^(x)\n==>P(X=x) = 37Cx * (0.75/0.25)^x * (0.25)^(37)\n==>P(X=x) = 37Cx * (3)^x * (0.25)^(37)\n\nTherefore, \nProbability of observiing 36 or more of the students who consider statistics to be an exciting subject\n==> P(X >= 36) = P(X=36) + P(X=37)\n\n\nP(X = 36) = C(37,36) * (3)^36 * (0.25)^(37)\nP(X = 37) = C(37,37) * (3)^37 * (0.25)^(37)\n\n\n\nhttp://www.futureaccountant.com/probability/study-notes/\n\nhttp://www.schoolingkids.com/
937106
Standard deviation tells us how far from the mean the data points tend to be.\n\nFor example, if the mean is 20 and SD is 5. Then all the numbers used to calculate the average (20) can be 5 standard deviation away from it. So the numbers can be from anywhere of 15-25.
408294
in statistics what you do is take a small sample, do the tests on the small sample and then generalize the results to the whole population.\n\nHere you took a small sample, found the mean to be 0.68\n\nBut the mean in the whole population will not be always equal to 0.68 . It can be 0.68, but it can lie anywhere around it to. \n\nHence, we have our confidence intervals around 0.68\n\nSo, when we say that the confidence intervals are (.63692, .72308), it means that we are 95% sure that the whole population mean will lie between 0.63692 seconds and .72308 seconds. \n\nSince 0.75 is not in that range, the chance of the population mean being 0.75 is less than 5% or negligible. \n\nI hope that helps.