**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)**

Where:

**n** = sample size

**N** = population

**e** = margin of error

**Example:**

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%**.

Solution:

**N** = 500

**e** = 100 – confidence coefficient

**e** = 5%

Since the **confidence coefficient** is **95%**, the **margin of erro**r 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.

**Raosoft**

Nowadays, researchers used other ways of getting a sample size. One of that is **Raosoft**.

To compute for sample size using Raosoft, kindly visit http://www.raosoft.com/samplesize.html

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 http://www.gpower.hhu.de/en.html

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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