Quote:
Originally Posted by Schatze  1.) Dichotomize populations into the subjects in the test and and normal group (teens in this study who wear hoodies and their liking of Linkin Park), and individuals who are not like those in the study.
State research and null hypothesis. Depending upon the method you're using, this may be as simple as mu1 != (use dashed equals sign) mu2 (the fancy U symbol that means population).
2.) Determine the characteristics of your distribution;
What distribution they'll fit in (T, F, Z, Chi square). Also the degrees of freedom if that is applicable. Some profs will want you to put other bits of information here
3.) Determine the cutoff score for your particular data set using your degrees of freedom, number of participants, alpha (.05, .01). Whether the test is one tailed or two tailed, if that particular distribution and type allows for it. Something like T critical one tailed = xxx.xx(df1), p. < .05, xxx.xx is looked up on a table
4.) Do your calculations here (or in space provided), to determine if your sample's score exceeds the critical value for the cutoff as found on a handy table.
5.) Decide whether to reject the null hypothesis; i.e. teenagers in hoodies do listen to Linkin Park at a greater level than the population at large
If you can't manage to memorize what you do where in a 5 step hypothesis test, you're going to be in major shit remembering the formulas. And if you need someone to hold your hand through explaining how each of the 5 steps works for T tests of various sorts, F tests, Z test, ANOVA, Chi-Square test, linear regression, etc., you're boned, because I went to classes and got As, so I have little sympathy for someone who probably skipped :P
I'm honestly confused though, you mention transferring so I assume you mean university, but a month on the 5 steps of hypothesis testing? Wut? We spent 15 minutes on it and then applied it for all the various parametric and a couple non-parametric statistical methods. THat was 2101 stats. Advanced lab stats was parametric and non-parametric stats with a heavy focus on getting to know and love SPSS.
P.S. It might be helpful to say WHAT stats course you're in. I've done stats for psychology which is very, very different from stats for engineering, or even business stats. Also that wiki page sort of sucks as it uses computational formulas which you won't be using in modern stats class. Computational formulas are sort of useless in the modern teaching of stats. |
Ok, so after being thoroughly admonished in this thread I went back and now I can do hypothesis testing.
Except for one tricky little detail.
Step 5! I know how to reject or fail to reject, but the statement I have to make afterwards confuses me. I am not sure how to phrase it.
Say I am testing a claim that drug D is effective in over 80% of cases. My H0: p=0 and H1: p>.8
I do steps 1-4 and find that my Z score is not within the critical region and so I fail to reject. What would my conclusion be and why? What if the z score was in the critical region and I rejected the H0?
I am taking introductory statistics. It is an online class (through the junior college) so I have to self teach. Basically what happened is I found out I got into berkeley, got psyched and spent a week doing nothing but paperwork/scholarships, and fucked myself over with chapter 8 (hypothesis testing). All i needed was a little explaining from someone who understands it, which i dont get much of for this course.
Right now I am starting chapter 10 (9 was "inferences from two samples" and 10 is "correlation and regression"). I only have two weeks before finals so I dont have a lot of time, which is why i am asking for assistance here for the things i am fuzzy with.
Thank you for the help!