The material covers the T-stat in both chapters but the formulas are different. Can anyone explain?作者: ramdabom 时间: 2011-7-13 16:32
can you post the formulas?
For a t stat test I believe it is
(X - M) / (S/(n^.5))作者: Micholien 时间: 2011-7-13 16:32
haha. Sorry for all the questions. But, I REALLLLYYYYY don't want to fail this thing and re-write it in June 2010. I find that with stats you gotta really understand the formulas and not just try and memorize them...作者: JPSem 时间: 2011-7-13 16:32
post context and formulas作者: waldziuchna 时间: 2011-7-13 16:32
The zstat, tstat and the test statistic (hypothesis testing) are essentially all the same from a conceptual perspective.作者: Finalnub 时间: 2011-7-13 16:32
Hi guys,
I'm confused over the relationship or differences between the following:
Sampling and Estimation:
t-stat: (point of estimation of the population mean) +/- (reliability factor t-stat) X (standard of error)
Hypothesis Testing:
z-stat: (sample mean - hypothsized mean)/ (standard of error)作者: burnsy562000 时间: 2011-7-13 16:32
Sampling and Estimation:
t-stat: (point of estimation of the population mean) +/- (reliability factor t-stat) X (standard of error)
* This is used for confidence interval for two-tailed distribution
while
Hypothesis Testing:
z-stat: (sample mean - hypothsized mean)/ (standard of error)
The above is the general formulae. If variance is known, it will be z-distribution. And if variance unknown, its for t-distribution.作者: MonkeyBusiness 时间: 2011-7-13 16:32
so how do you know when to use which?作者: Wasteoftime 时间: 2011-7-13 16:33
For
(point of estimation of the population mean) +/- (reliability factor t-stat) X (standard of error) ;use this when the Qn ask for Confidence interval. The reliability factor is also the "critical value" (Read from the table) For the <standard of error> you can imagine it to be Standard deviation in your bell curve.
And for
(sample mean - hypothsized mean)/ (standard of error) ;
this is to find the z/t statistic of which you will compare it with the critical value and decide (depending if its two-tailed or one-tailed) if to reject null hypothesis.
To use t statistic, when population variance is unknown and you have small sample size(n<30).
For z-statistic, you use when you the population variance is known. You can also use z-statistic, when the population variance is unknown and n>equal to 30. As large sample tends to the normal distribution.
For the above formulae, its a general one. Mean - given usually. hypothesized mean - mean you based your hypothesis on. and the standard error -> can be found using both pop standard deviation & sample standard deviation divide by the sq root of size n.
