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Student's t-test (For Paired samples) calculation

Hi everyone,

I'm doing my project on developing a tool for statistical techniques used in micro-array data analysis. For that i selected few techniques such as Student's t-test, P value, Z-Score, and so on. Now i couldn't find a proper algorithm or the steps for calculating t-test for paired samples. So, Please help me in that.

Thank you in advance.

microarray

Sorry I didn't get you. Are you asking me about the programming language which I'm using.

Thank you for that. If possible can you give me the formula for calculating it.

Here is a formula. By the sounds of things you're more of a CS person (apologies for the blunt assumption), so I'd consider consulting with a statistician to make sure you've got everything right in your code / head.

Thank you. I saw that and found it's so useful. Thank you once again.

This is an excellent article, assumptions and explanation are really so good, All your contributions are very useful for professionals and non-professionals. Thnaks a lot for sharing a awesome article, Keep on posting.

2 answers

to compare values x and y in R:

x <- rnorm(10,0,1)
y <- rnorm(10,2,1)
x
 [1] -0.6576916 -0.2038356  0.4096263  1.1366582 -1.0279443 -0.9268312
 [7]  2.0242495 -0.6359770 -0.1778478  0.7623316
y
 [1]  3.4962164  0.6779518  2.1233511  2.8031245 -0.4187195  0.9020173
 [7]  2.0746169  4.3182421  0.4239949  3.4268671
t.test(x,y,paired=T)

    Paired t-test

data:  x and y
t = -3.7919, df = 9, p-value = 0.00427
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
 -3.0534517 -0.7715332
sample estimates:
mean of the differences 
              -1.912492

Thank you for your response. By i'm doing my project in java.

No need to re-implement that, please check for existing libraries and software first:

https://commons.apache.org/proper/commons-math/jacoco/org.apache.commons.math3.stat.inference/index.html

There are also existing complete Java microarray systems:

T-test is not necessarily the best tool for doing DE in microarrays, check for limma, cyberT, SAM.

Finally, microarrays are a dying technology.

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