Statistics

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SAMPLE SIZE CALCULATION

http://www.openepi.com/SampleSize/SSPropor.htm

http://riskcalc.org:3838/samplesize/

http://statulator.com/

https://sample-size.net/correlation-sample-size/

https://epitools.ausvet.com.au/samplesize

https://www2.ccrb.cuhk.edu.hk/stat/

https://sphweb.bumc.bu.edu

https://www.scistat.com/samplesize/

P Value vs Alpha level

Alpha levels are controlled by the researcher and are related to confidence levels. You get an alpha level by subtracting your confidence level from 100%. For example, if you want to be 98 percent confident in your research, the alpha level would be 2% (100% – 98%). When you run the hypothesis test, the test will give you a value for p. Compare that value to your chosen alpha level. For example, let’s say you chose an alpha level of 5% (0.05). If the results from the test give you:

• A small p (≤ 0.05), reject the null hypothesis. This is strong evidence that the null hypothesis is invalid.

• A large p (> 0.05) means the alternate hypothesis is weak, so you do not reject the null.

What if I Don’t Have an Alpha Level?

In an ideal world, you’ll have an alpha level. But if you do not, you can still use the following rough guidelines in deciding whether to support or reject the null hypothesis:

• If p > .10 → “not significant”

• If p ≤ .10 → “marginally significant”

• If p ≤ .05 → “significant”

• If p ≤ .01 → “highly significant.”

https://www.statisticshowto.com/probability-and-statistics/statistics-definitions/p-value/