It depends on the hypothesis test and the situation at hand. Common ones are when you have asymptotic normality under a null hypothesis (which is often the case from the Central Limit Theorem), you can use a Z-test ( https://en.wikipedia.org/wiki/Z-test ), or you could use a Chi-Squared test sometimes. Depends on what purpose the test is serving.Any tips on what test statistic to use for a hypothesis test?
Oh I double checked that. I put the n back in there, got a determinant of (2alpha beta^2)/n^2 * (a matrix with n's appearing everywhere). That's fine I reckonAlso I think the final answer's denominator should be n^2 (not n).
When we were taught it, we were honestly taught "educated guess". Normally I try to exploit the CLT.Any tips on what test statistic to use for a hypothesis test?
Oh yeah, I forgot to include the n in front of the matrix when getting the 1,1 entry of the inverse. It should be n in the denominator indeed (for final answer).Oh I double checked that. I put the n back in there, got a determinant of (2alpha beta^2)/n^2 * (a matrix with n's appearing everywhere). That's fine I reckon
When we were taught it, we were honestly taught "educated guess". Normally I try to exploit the CLT.
We don't know it ("it" refers to the population standard deviation (or really the standard deviation of the assumed underlying distribution)), since that's only the sample standard deviation.Also I read that if standard deviation / sigma is know, we can use z-distribution. If not, use t-distribution. We're given the sample SD right?? Does that mean we know it or not?
You leave it there. They will supply you the R code and all you have to do is read it.Help pls someone,
So we have to use R commands instead of distribution tables (wtf it's so much easier with the tables)?
How would you then find the region of rejection (when doing a hypothesis test) for both z and t distributions?
E.g. for T test, I would find the degrees of freedom (n-1), and look up n-1 on the T table with the respective value of alpha, say 0.05. How would you do this in the test????
yeah I am a mind reader that knows what vaguely named functions doYou leave it there. They will supply you the R code and all you have to do is read it.
Since you do computer science you shouldn't have any trouble understanding just one line of code tbh
R's free to download. You can always just investigate brieflyyeah I am a mind reader that knows what vaguely named functions do
But anyway I know it's just going to be a shit show. Hopefully not, but I am 80% sure it will be.
ThanksR's free to download. You can always just investigate briefly
Here's an example of something that might appear
Tbh all I've seen is p___, q___, r___ where ___ is a distribution.
p - probability
q - quantile
r - just a bunch of random simulations
You could try the 2901 exam past papers just in case, as they seem to be similar difficulties (I think some questions overlap? or the old ones used to anyway.)Thanks
tbh I think I will fail this course unfortunately
We learn this in second year at UNSW, so it seems a bit later than at Macquarie.All this stat stuff looks so much more complicated than what I've done. Only done stat171 where had z, various t tests, and chi squared test for independence and GOF test... rip
I think youre supposed to make the null hypothesis equal to something but it doestn really matter so I guessCan you guys help me with going through this question:
So to start off, is the null and alternative hypothesis.... H0 = 95 versus H1 < 95. Or is this wrong??
OR is it H0 < 95 versus H1 >= 95
I think it should be Ho: U = 95, Ha: U < 95I think youre supposed to make the null hypothesis equal to something but it doestn really matter so I guess
This is how I would do it