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How To Get A Reliable Sample Size For Your Project Work - Education - Nairaland

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How To Use Sample Size Calculator For Sample Size Calculation / Calculating Sample Size Using The Taro Yamane Formular / Use This Awesome Tool To Calculate Accurate Sample Size From Your Population. (2) (3) (4)

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How To Get A Reliable Sample Size For Your Project Work by gomtas: 1:21pm On Aug 09, 2018
During research works, most researchers or project students find it difficult to calculate the adequate sample size of their project research work. The determination of sample sizes comes up before questionnaires are drafted and sent into the field to get data for analysis. Miscalculation of sample sizes may lead to outright cancellation of research/project work by project supervisors as conclusions reached from the uncalculated sample size would not be precise enough in making a generalisation on the hypothesis under study.

The essence of adequate calculation of sample sizes is so that the conclusions reached after analysis can be generalized to the entire population under study.

As a result of our love for research, we have decided to teach students and researchers on the most reliable and effective way of calculating sample size for their project and research works. Below is one of the generally accepted methods in sample size calculation


THE TARO YAMANE METHOD

Taro Yamane , a mathematical statistician developed a statistical formular for calculating or determination of sample size in relation to the population under study so that inferences and conclusions drawn after the survey can be generalized to the entire population from which the sample was gotten.

The Taro Yamane statistical formular is thus:


n = N/ 1+ N(e)2

In the formular above;

n is the required sample size from the population under study

N is the whole population that is under study

e is the precision or sampling error which is usually 0.10,0.05 or 0.01

Example:

Using the Taro Yamane’s statistical formular to determine the adequate sample size of say 300 respondents under study. This would hence be



n = N/ 1+ N(e)2

N=300; e= 0.1; e2= 0.01

n = 300/1+ 300(0.1)2

n= 100.

Therefore, a sample size 100 respondents out of the entire population of 300 respondents would therefore be the lowest acceptable number of responses to maintain a 95% confidence level.

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