Help with Statistics (interpreting excel)!!!

[theholygideons]

I know this is the wrong section, but it won't let me attach files in the 'everything but piano' section.

I'm doing a t test assuming equal variances on excel.
It gives that the P(T>t) = 0.020883<0.05, for 2 tailed. Which means reject the null hypothesis.
but then if you compare Tstat and t crit, you get Tstat=-2.795<tCrit=2.262157. Which should mean accept null hyothesis.

Isn't that a contradiction??
Thanks.

[theholygideons]

bump

[brogers70]

I believe you just look at the absolute value of the t statistic. The sign will change depending on what group you call group 1 or group 2. So there's no contradiction; you should reject the null. Just out of curiosity, though, note that although you assume equal variance, the variances in the two groups are not equal. I doubt that will cause a problem big enough to make you unable to reject the null, but you can do a t-test that accounts for unequal variances - I think it is an option in excel.

[theholygideons]

I believe you just look at the absolute value of the t statistic. The sign will change depending on what group you call group 1 or group 2. So there's no contradiction; you should reject the null. Just out of curiosity, though, note that although you assume equal variance, the variances in the two groups are not equal. I doubt that will cause a problem big enough to make you unable to reject the null, but you can do a t-test that accounts for unequal variances - I think it is an option in excel.

I did a fischer test on the variance, and there isn't a significant difference between them. The absolute value eh.. interesting!!! excel lies!!!

[Bob]

I wonder if the attachment will stay if you move the thread to another board.  Could be interesting.

[brogers70]

I did a fischer test on the variance, and there isn't a significant difference between them. The absolute value eh.. interesting!!! excel lies!!!

I'm not sure Excel exactly lies, but it's not a great program for statistics. I'm a retired infectious disease epidemiologist; I used to use the program Stata for statistics. It's pretty easy to use (menu-driven) and it covers almost everything you're likely to need unless you are doing very complex analyses on huge databases. I've heard SPSS is good for social science statistics, but it's not quite as good for epidemiology as Stata. The monster was always SAS - that was driven by commands without a menu and folks who learned it were very attached to it, but unless you needed to do something very tricky, I don't think it was any better than SPSS or Stata.

[theholygideons]

I'm not sure Excel exactly lies, but it's not a great program for statistics. I'm a retired infectious disease epidemiologist; I used to use the program Stata for statistics. It's pretty easy to use (menu-driven) and it covers almost everything you're likely to need unless you are doing very complex analyses on huge databases. I've heard SPSS is good for social science statistics, but it's not quite as good for epidemiology as Stata. The monster was always SAS - that was driven by commands without a menu and folks who learned it were very attached to it, but unless you needed to do something very tricky, I don't think it was any better than SPSS or Stata.

That's so interesting!! to think that I will have to use all these programs. I'm studying medicinal chemistry, and my lecturer for analytical chemistry reasons that no matter on which computer you're on, you're bound to have excel, haha. On a side note, my lectures on applied statistics seem incredibly arbitrary and poorly written, I feel like I have to self-learn everything in detail before I can apply it in practise.

[brogers70]

If your text is not that clear, I recommend this

 https://www.amazon.com/Primer-Biostatistics-Seventh-Glantz-Paperback/dp/0071781501/ref=sr_1_1?s=books&ie=UTF8&qid=1395505817&sr=1-1&keywords=primer+of+biostatistics

It's Primer of Biostatistics, by Stanton Glantz. I used an earlier edition to teach an intro class on statistics. Even though it's called a primer of Biostatistics, there's nothing really specific to biology about it. It's a good, straightforward treatment of many common statistical tests. It's strong point is that it emphasizes understanding the importance of variance rather than just doing significance testing.