HOW TO CALCULATE A RELAIBLE SAMPLE SIZE USING TARO YAMANE METHOD

December 3, 2016. IMPERIAL WRITERS

In the academic environment especially the research aspect of it has seen sample size as one of the most vital character in statistics. The basic for a research based on primary data uses sample size as the starting point.

Most project/research students find it difficult to get a reliable sample size for the research works. We found it very importance to use this medium to educate project students on how to calculate sample size using TARO YAMANE method.

Sample size determination plays a significant role in research that uses primary data seeking responses from the use of questionnaires.

When the questionnaire for the project topic is drafted, the research students are expected to know the population they are distributing the questionnaires to, after the distribution, the research students are expected to calculate their sample size from the population they administer the questionnaires to. Lets us see how we can calculate a reliable sample size using Taro Yamane method.

 

TARO YAMANE METHOD

The Taro Yamane method for sample size calculation was formulated by the statistician Tara Yamane in 1967 to determine the sample size from a given population. Below is the mathematical illustration for the Taro Yamane method:

n= N/ (1+N (e) 2)

Where:

n signifies the sample size

N signifies the population under study

e signifies the margin error (it could be 0.10, 0.05 or 0.01)

We will illustrate with the above formula to determine the sample size from a given population.

Take for example a project a student have a total population of about 400 respondents and wishes to determine the sample size. See below:

n= N/ (1+N (e) 2)

Where:

n signifies the sample size

N signifies the population under study

e signifies the margin error

n= 400/ (1+400(0.05)2)

n= 400/ (1+ 400(0.0025)

n= 400/ (1+1)

n= 400/2

n= 200

We can see from the result above that the sample size is 200 from the total population of 400 which is the lower number of responses from the respondents to maintain a 95% confident interval.

I believe this could help our esteemed researcher in Nigeria and all over the world.