It looks like you've provided the data for a confidence interval calculation. Here’s a breakdown of the information you’ve given:

(a) Summary of given data:

• Mean (x̄) = 2.21%
• Standard deviation (s) = 1.34%

(b) 90% Confidence Interval:

• Lower limit = 1.75%
• Upper limit = 2.67%

(c) 99% Confidence Interval:

• Lower limit = 1.51%
• Upper limit = 2.91%

Interpretation:

The provided values are for the confidence intervals of a population parameter based on sample data. These intervals estimate the range in which the true population mean is likely to fall with a specified level of confidence.

For example, with the 90% Confidence Interval (1.75% to 2.67%), you are 90% confident that the true population mean lies within this range. Similarly, for the 99% Confidence Interval (1.51% to 2.91%), the confidence level is 99%, meaning there is a higher certainty that the population mean falls within this range.

Do you need more clarification on how these intervals were calculated, or would you like to explore other related questions?

Here are 5 related questions:

1. How do you calculate a confidence interval for a sample?
2. What is the difference between a 90% and a 99% confidence interval?
3. How does the sample size affect the width of the confidence interval?
4. How can I interpret a standard deviation in the context of these intervals?
5. How would the confidence interval change if the sample standard deviation were smaller?

Tip: As the confidence level increases (from 90% to 99%), the confidence interval becomes wider. This reflects the increased certainty but also introduces a greater range within which the true mean could lie.