What are the similarities and differences between a z test and a t test ?
916981
actually a real life distribution approaches normal distribution as n approaches infinity.\n\nthat's why z-test got its name. it is used for large number of n.\nit approximate the normal distribution.\n\nactually, the formulas for these two test are the same.\nthe only difference is the the latter uses a parameter while the other uses statistic or estimate.\n\n\nwhen should you use each of them\n\nUSE Z-TEST IF:\n*n>30\n*the population mean is given\n*the population standard deviation is also given\n\n\nUSE T-TEST IF:\n*n<30\n*the population mean is not given\n*the population standard deviation is not also given
258372
Oh, I've had to learn nonparametric statistics from scratch, due to my research...\nThe Dunn test is a post-hoc or 'a posteriori' test that you use _after_ a non parametric ANOVA (I assume you know what that is) indicates that there are significant differences between the groups that you're comparing. \nThe non parametric ANOVA (normally it's the Kruskal-Wallis test) can only tell you that there is an _overall_ significant difference. \nThe Dunn test then compares each pair of groups and tells you which of these pairwise differences are significant.\n \nI don't know of any statistical package that performs it (if you do, please let me know) but it's not difficult if you construct an Excel worksheet with the formulas. You can find a good account of the calculations in Zar's Biostatistical Analysis book.
273970
No problem \n\ngo to google and search under "Z table" +statistics. \n\nYou'll find a lot.
878741
There are certain steps to perform a hypothesis test.\n\n1. Construct a null hypothesis Ho .\n2. Construct a alternate hypothesis H1.\n3. Decide test statistics and parameters [this includes degrees of freedom, significance value] [inmost cases its denoted by Z or t].\n4. Compute the p-value.\n5. Check with the available table.\n6. make inferences wether the hypothesis is accepted or not.\n\nThere is no fixed fomulae for this, but the choice of null hypothesis and test statistics depends on the problem. \n\nThe type of null hypothesis depends on the probelm(wether certain parameters are given or certain distributions are followed by given data etc) and the test statistics depends on parameters.\n\nI hope now you know it.\n\nAll the best
927712
there are tens of tests for one things, thyroid eg TSH, TRH, FT4, FT3, and many more, same for cholesterol, so say what you need specifically and someone could help you more, good luck
279794
figure out the efgfect of the enzyme. Or you can test DNA structure. Inhibitary enzymes have a blacked actionsite whereas activation enzymes have activation sites open to substrates
755974
You need to use the Student's T-Test.\n\nRead about it here:\n\nhttp://en.wikipedia.org/wiki/Student%27s_t-test
399013
As it happens, I just got back from a test on statistics. We covered that very question. \n\nHere goes:\nthe sample size is dependent on how confident you want to be about your results. In the following formula, then Z is the confidence level. Use 1.65 for 90% confidence level, 1.96 for 95%, 2,33 for 98% and 2.58 for 99%. \nYou also need to know the standard deviation, which should be given. and the error allowable, for instance 3%, or 5% or such. That number goes into the formula as E. \n\nso number n equals = (Z * standard deviation/E)^2
849629
Alpha, as related to level of significance, is purely up to the statistician.  It simply denotes how sure you are of your findings.  The p-value is more descriptive.  The p-value is basically the probability that the statistician will reject the null hypothesis when it in fact should not be rejected.  If the p-value is less than the chosen alpha level, the null hypothesis is rejected.
1158757
t-ray technology, basically work similar to x-rays the only difference is it focuses in on a molecules distinct vibration pattern, all molecules vibrate at different rate based on the item, so for instance if you set the machine to focus on the molecules in a spoon and you have one in your pocket it will show on the screen, same goes say for cancer cells even if they are the size of just one molecule, think stocks and big $$$$$ because the implinatation in different industries is unlimited, security, medical, construction, so on
1151074
One could perform a t-test for difference of means to see if there is a significant difference in the means using the range/4 estimate of the standard deviation.
721208
If you are talking about z scores for one particular variable, then you should use a histogram.  Excel does not do histograms, so you should probably use MINITAB or some other statistics program.\n\nThe previous answer only applies if there are two variables involved.
674991
For one-sample t-test, \nt = (sample mean - population mean) / estimated standard error. \n\nIn math notation, t = (X bar - mu not) / (s/sqrt(n))\n\nAssumptions: (normal population or sample size, n, is at least 30) and population standard deviation is unknown.\n\nThere are other variations of t-tests like two-sample(pooled and unpooled) and paired ...
10461
There is no difference in spots. The male and female are hard to tell apart other than the female is slightly larger. Otherwise you have to use a microscope.
253231
They both test differently... I think both should be used.  hey need to reformat the test to not be gender or ethnically biased but otherwise, combined, they are great tools.
835937
There is very little correlation between the two tests - there are 3 sections (2 reasoning and 1 games) on the LSAT that have no equivalent on the SATs, the reading has a different focus, and the whole test is scored very differently. However, you can easily see what score you can get by taking a free practice test - Kaplan offers them on most major university campuses in February. Check it out and see!
862471
Your going to compare your mean with the population mean and see if your class really better than the average of the population.\nHo: u = xbar\nHa: u < xbar\n\nalpha = 0.10\none tailed test (of course)\ntherefore: z(table) = -1.28 (i'm not sure)\n\nuse z test since you know the population standard deviation.\n\nz = (x - u)/o/sqrt of n\n\nthat's it.\n\ngood luck