APLUSA Stats 2.3.4

Here is a professional review of three commonly utilized statistical tools for analyzing market research results:

• 1 - Confidence Interval Calculator
• 2 - Comparing Two Percentages
• 3 - Sample Size Calculator

1 - Confidence Interval Calculator

This tool estimates the accuracy of proportion measurements obtained from sample surveys. As the sample size increases, the statistical confidence in the results also improves. The confidence interval indicates the range within which the true population parameter is likely to fall, given a specified level of confidence.

For example, consider a survey of 500 general practitioners (GPs), where 20% report using Product A. What is the estimated proportion of Product A users in the entire GP population?

Assuming a 5% risk level (confidence level of 95%), the confidence interval is approximately:

• 20% ±3.5%
• [16.5% – 23.5%]

This suggests there is a 95% probability that the actual proportion of Product A users among all GPs falls between 16.5% and 23.5%.

2 - Comparing Two Percentages

This analysis assesses whether differences observed between two sample proportions are statistically significant. Significance testing determines if such differences are likely to reflect true variations in the population or are attributable to sampling variability.

For example, suppose a survey of 500 GPs finds that 20% use Product A, while a separate survey of 150 cardiologists finds that 25% use the same product. Does this indicate a meaningful difference?

With a 5% significance level (95% confidence), this difference is not statistically significant, implying no reliable evidence that cardiologists have a higher usage rate than GPs.

In essence, there is a high probability that the true usage proportions are similar across these professional groups.

3 - Sample Size Calculator

This tool helps determine the minimum number of respondents required to achieve a desired confidence interval, based on an expected proportion and an acceptable margin of error. It facilitates proper planning for market research where resource allocation and accuracy considerations are crucial.

For instance, consider evaluating Product A's usage among anesthetists, with a target confidence interval of ±8%. If approximately one-third are expected to use the product, what sample size is necessary?

At a 5% risk level (95% confidence), with an anticipated proportion of 33%, the minimum sample size required is approximately 133 anesthetists.

This means that surveying at least this number guarantees with high probability that the true proportion falls within the specified margin of error.