I'm new here. I found this place on Google after two days of studying like mad and not understanding anything. well, sort of. Let me explain:

I'm a nursing/health sciences student, sophomore year, taking stats and research methods for health sciences. I hate this class so much. *cries* I mean, the teacher is really great and nice, but not only is it STATS, a hard math class (I'm absolutely horrible at math!), but it's not even normal stats! my bf and the school tutoring services helped me pass College Algebra last semester, to where I actually understood things. but even people who understand stats are confused by the terms and stuff in my class! and my teacher basically told me I was on my own for finding a tutor... she is nice though-- she offered to let me retake the stats test this Monday afternoon (but I actually think I'll have to do it in the morning. =/). So I kind of want to have some idea of what on earth I'm testing on...

okay, according to my book, we're studying null and alternative hypotheses. from what I understand, a null hypothesis is the pre-assumed, accepted concept. (The sky is blue) The alternative hypothesis is challenging the null hypothesis (The sky is not blue).

Also we have one-tailed and two-tailed t tests. it has something to do with 'Student's' t test. if the alternative hypothesis (H1) is 'the sky is different than blue', it's a two-tailed test and myu/population mean is = or not =. if it's 'the sky is less than/greater than blue', you use > or < and it is a one-tailed/one-directional test.

We're also dealing with critical values and critical regions. I *think* that how it works is that if the t or z score is in the critical region you fail to reject the null hypothesis (H0) because it's not significantly different/greater than/less than the actual results. or something. and you do reject it if the t score is outside the critical value.

And then there's confidence intervals... I sort of know how to do them, sort of. That has to do with stating your confidence that 95 or 99 of 100 groups with the same sample size as yours will have the same test results.

And we're doing something called independent and dependent/paired t tests... it has to do with something called two-sample t tests. instead of comparing the sample mean to the population mean, you compare the two samples to each other. I guess that if they're different at all, the two samples are independent. and if they have the same number of people and stuff, they're dependent.

We have to do pre and posttest stuff with paird t tests... I really don't understand this at all. I was a straight A student until college algebra, and now I'm struggling to even pass stats... I have to make a C in this class to have any kind of a future in the health care field, and all I want to do is take care of people. I should have just waited and taken this class someplace else, like a school that isn't so weak in the math/sciences department (I'm transferring this fall, but that doesn't help me right now). It's way past the deadline to withdraw, and even if I could I'd lose all my scholarship money. I'm so stupid and I hate myself and probably don't even deserve any help, but I promise if someone can just please help me understand I'll work so hard to understand! =( I might need to IM with someone to 'get it', so if you have pity on me (lol) and want to help, please please PM me and I'll give you my various handles... I'm so stressed! please, if anyone can help at all, I would be forever grateful!

Thanks,

-Rachel