The sample size calculator

Power analysis and sample size calculation are important planning stage of the experiment, because without these calculations, the amount of data may be too large or too small to obtain reliable results.
If the sample size is too small, you have small probability that you have carried out an experimental research (mass survey, etc.) will give reliable results. On the contrary, if the sample size is too large, the time spent on data collection and large financial costs associated with it, will not bring the expected effect.

Web app “Sample size calculator” will help you to solve this task!

More detail you can get in “Introduction” page in app.

Parameters meaning in calculator:
1) Power - power of test (1 minus Type II error probability)
Power is usually fixed at 80%, 90% or 95%. Power must not be less than 80%.
2) The effect size - the difference in the means in standard deviation units (difference in the means / standard deviation).
3) Type of t test.
4) One- or two-sided test.

calcSize <- round(power.t.test(power = 0.9, 
                 delta = 1, 
                 sd = 12.5, 
                 type = 'two.sample', 
                 alt = 'two.sided')$n , 0)
calcSize

[1] 3285

Link to project on GitHUB

Link to app on Shinyapp