Hi,

For some reason MeV gives different p-values for t-test than both Excel and R. For example, I have these 6 numbers:

GroupA: 179.7673133 109.2865837 155.4898853

GroupB: 109.6793997 100.727767 140.8898293

I load it to MeV (latest version but same results with older versions as well) as single color array. Then I select t-test and use "Between subjects" test with Welch approx. The rest is default. I get correct means and st.dev but I get this raw p-val 0.26480287 (adj p-val is the same). In excel it is: 0.279720154 (two-tailed, unequal variance t-test). First I assumed that Excel is wrong but here is what I get in R:

t.test(c(179.7673133,109.2865837,155.4898853),c(109.6793997,100.727767,140.8898293))

result is:

Welch Two Sample t-test

data: c(179.7673133, 109.2865837, 155.4898853) and c(109.6793997, 100.727767, 140.8898293)

t = 1.2957, df = 3.238, p-value = 0.2797

alternative hypothesis: true difference in means is not equal to 0

95 percent confidence interval:

-42.18235 104.34688

sample estimates:

mean of x mean of y

148.1813 117.0990

Another example:

GroupA: 416.8104479 371.4943213 414.9956691

GroupB: 263.326655 279.695355 215.8603682

MeV p-val: 0.008767734

Excel, R p-val: 0.004396191

Strange … What is the difference in t-test in Excel and R versus t-test in MeV? I could not get the same numbers with any settings of MeV.

Any idea?

Marek