# Search results

1. ### How to compare two sample populations?

I fear that to do this exactly would require t distributions (not just cut points) and possibly non-central t, which is not something I work with. To do it roughly, calculate the standard error of the difference of means from your population SD (which must be 0.36, not -0.36, since an SD cannot...
2. ### Statistical analysis in Genetic

I think the issue, that you correctly recognize, is that the related patients probably have a lot of genetic variants in common, by virtue of being related. They may have genes for eye color, hair color, freckle type, etc... in common, all having exactly nothing to do with GH deficiency. I...
3. ### Correlation between the dependent variables in an experiments (Urgent )

OK, I see what you did. These correlations seem logically very low (in other words, we would expect some correlation between, say, engagement and ease of use) but the fact that both increased doesn't mean that there should be one. Imagine having classes that trained on algebra and reading...
4. ### Am I dealing with outliers, or something else (skewness of 106)?

Don't know as I've ever seen a skew of 106 in real data -- cool! (Until you have to analyze it). I gather a log transform didn't work. People sometimes convert data like this into quarters or fifths. In some cases a dichotomy makes sense, *if* there is a logical cutpoint. You might argue...
5. ### Correlation between the dependent variables in an experiments (Urgent )

As children get older their vocabularies increase, as do their absolute muscle strengths in the bicep muscle. But I expect no correlation between those two variables at any age. I al not quite clear what you are correlating, however. You must have measured each variable twice on each subject...
6. ### 95% confidence interval using standard error of a proportion

I see another person (OBH) chimed in, but I fear he or she is doing it wrong. OBH is starting with the observed proportion and figuring out what a range of values that would occur with 95% probability if that was the population proportion. It may not make a huge difference, but believe the...
7. ### 95% confidence interval using standard error of a proportion

I would recommend using the exact method. Do it in Excel. =1-BINOM.DIST(48,50,0.90,TRUE) This formula calculates the probability of getting from 0 to 48 successes in 50 trials if the probability on each trial is 0.9. This is then subtracted from 1 to give the probability of getting *more*...
8. ### How to correct for comparisons between and within groups?

Obviously, if the data were normal, we would start with a 2-way ANOVA to look for the group by time interaction. If the data are not too badly non-normal, I might do that anyway. It provides a nice support for the follow-up tests. If the interaction is entirely NS, you have no basis for most of...
9. ### Pearson vs. Spearman coefficient

Good point. Actually it looks like most people prefer Kendall's tau for many tied observations over any form of Spearman in that case.
10. ### Pearson vs. Spearman coefficient

In my opinion, there is a good argument for using Spearman correlations anytime you have a Likert scale variable (1-5, say) because the data in such a scale is not interval level measurement. We don't know that the difference between 1 and 2 has the same meaning as the difference between 2 and...
11. ### Looking for appropriate loop

Hm, this shows nice indenting when I edit it, but removes all the indents when I view it. Hope you can see the indents -- much easier to figure out.
12. ### Looking for appropriate loop

How about something like Do repeat KX = k1 to k5. Compute KX = 0. end repeat. Do repeat px = P1 to p20. ST = 0. Do if px > 0. do repeat ky = k1 to k5. do if ky = 0 and ST = 0. ky = px. ST = 1. end if. end repeat. end if. End repeat. I haven't...
13. ### Appropriateness of p-value in my data

It looks like your analysis program included the continuity correction (since I get 0.017 one tailed using continuity corrected chi-square). You may want to see if you need to use that stricter version, based on the expected cell frequencies. The uncorrected chi-square gives a smaller p value...
14. ### Simple Question

Not quite sure what you mean by "at least 1 to 100". Do you mean "at least 100"? No, I am not confident that it would be at least 100. We expect *around* 100, but it could easily be more or less. // And of course the whole question assumes a random group of shoppers. If this is a high end...
15. ### How to deal with an Odd Number in Chi Square?

Why not? In contingency table chi-square, the expected values are often non-integer. Same for GOF.