Use Python to determine the optimum sample size

Calculating sample sizes is crucial in statistics and research for several reasons, namely being cited for:-

1. Accuracy and precision ensures representative and precise results.
2. Statistical power increases the ability to detect true effects.
3. Validity of results enhances the trustworthiness of conclusions.
4. Resource efficiency optimises the use of resources.
5. Ethical considerations minimise unnecessary involvement of subjects.
6. Generalisability improves applicability of findings to the population.

As an example of calculating the correct sample size when conducting statistical research would be to research the effectiveness of a new medication. If the sample size is too small, the study might not detect a real difference between the treatment and control groups, leading to inconclusive or inaccurate results. A sample size that is too large, on the other hand, might unnecessarily consume resources and time.

The steps to take to calculate the sample size are:-

1. Define the parameters of population size, confidence level, margin of error, and population standard deviation or population standard proportion.
2. Calculate the z-score or t-score. Find…