# What is the sample size of 839000 population using the Taro Yemani formula.

#### 2 answers:

#### Rainnjazz *Nov. 30, 2023*

The Taro Yemani formula is used to determine the sample size needed for a given population with a desired level of confidence and margin of error. The formula is: n = (Z^2 * p * q) / E^2 where: n = sample size Z = Z-score for desired level of confidence (e.g. for 95% confidence, Z = 1.96) p = estimated proportion of population with desired characteristic (if unknown, use 0.5 for maximum variability) q = 1 - p E = desired margin of error (e.g. +/- 3%) Using this formula for a population of 839000 and a desired margin of error of +/- 3%, with a 95% confidence level and assuming maximum variability (p = 0.5), we get: n = (1.96^2 * 0.5 * 0.5) / (0.03^2) n = 1067.11 Therefore, the sample size needed for a population of 839000 with a desired margin of error of +/- 3% and 95% confidence level using the Taro Yemani formula is approximately 1067.

#### muhalhq *Dec. 17, 2023*

To calculate the sample size of 839000 population using the Taro Yamane formula, Desired confidence level: This typically ranges from 90% to 95%. A higher confidence level means a larger sample size. Margin of error: This is the maximum acceptable error you are willing to tolerate in your sample's estimate. A smaller margin of error means a larger sample size. Estimated proportion (p): This is the proportion of the population you expect to have the characteristic you are interested in. If you don't have a good estimate, you can use 0.5 (assuming maximum variability). Once you provide these values, I can plug them into the Taro Yamane formula: n = (Z^2 * p * q) / E^2 where: n is the sample size Z is the Z-score for your desired confidence level (e.g., 1.96 for 95% confidence) p is the estimated proportion q is 1 - p E is the desired margin of error For example, if you want a 95% confidence level with a 3% margin of error and assuming maximum variability (p = 0.5), the sample size would be: n = (1.96^2 * 0.5 * 0.5) / (0.03^2) ≈ 1067 Therefore, you would need a sample size of approximately 1067 for your study.

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