In Getting a Sample Size From a Population, What Should I Use?

Slovin’s Formula
Over the years in the field of research, researchers used Slovin’s Formula in identifying sample from a given population that will serve as their respondents. This is used to calculate the sample size (n) given the population size (N) and a margin of error (e).
The formula is n = N / (1+Ne^2)
n = sample size
N = population
e = margin of error

There are 500 Grade 11 senior high school students in Luis Y Ferrer Jr. Senior High School. Find the sample size from the given students with a confidence coefficient of 95%.
N = 500
e = 100 – confidence coefficient
e = 5%

Since the confidence coefficient is 95%, the margin of error is 5%.
n = 500 / (1 + 500(0.05)^2
n = 500 / 2.25
n = 222 students
However, different researchers assumed that they can use always Slovin’s Formula in any situation in getting the sample size giving us the wrong impression that we can use it in any sampling problem.
Please read the article, “On the Misuse of Slovin’s Formula” for more details.

Nowadays, researchers used other ways of getting a sample size. One of that is Raosoft.
To compute for sample size using Raosoft, kindly visit
The page will automatically compute for the sample size with the given margin of error, confidence level, population size, and response distribution.



G Power
Another tool used for sample size calculations is G Power. It is a free, open-source program for statistical power analysis such as different t-tests, F tests, χ2 tests, z tests and some exact tests, and sample size calculations. It is available for both Windows and Mac.
To download G Power, kindly click
Click here to download G Power manual: Download the G*Power manual (PDF)

If you are using G Power in your research, kindly add the appropriate reference on your research for proper citation:
Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175-191. Download PDF

Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41, 1149-1160. Download PDF


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