Confidence level

Definition

Confidence level represents the percentage of all possible samples that can be expected to include the true population parameter. It indicates the degree of certainty associated with a confidence interval.

5 Must Know Facts For Your Next Test

1. The most common confidence levels are 90%, 95%, and 99%.
2. A higher confidence level means a wider confidence interval.
3. Confidence level is denoted by (1 - α), where α is the significance level.
4. Increasing sample size can reduce the margin of error while maintaining the same confidence level.
5. The critical value corresponding to a given confidence level can be found using the standard normal distribution.

Review Questions

• What does a 95% confidence level signify in terms of population parameter inclusion?
• How does increasing the sample size affect the width of the confidence interval for a fixed confidence level?
• What is the relationship between significance level (α) and confidence level?

Related terms

Confidence Interval: A range of values derived from sample statistics that is likely to contain the true population parameter.

Margin of Error: The maximum amount by which the sample estimate may differ from the true population parameter within a given confidence level.

Significance Level (α): The probability of rejecting the null hypothesis when it is actually true, typically set at 0.05, 0.01, or 0.10.