Confidence Intervals and Estimation Flashcards
6 cards from real FAST practice questions. Tap to flip, then mark Knew It or Still Learning — missed cards come back until you master them.
Read the first 6 Confidence Intervals and Estimation flashcards as text
What does a 95% confidence interval mean?
Answer: If we repeated the sampling many times, 95% of the intervals would contain the true parameter
A 95% confidence interval means that the procedure used will capture the true parameter 95% of the time across repeated samples.
What happens to the confidence interval as sample size increases?
Answer: It becomes narrower, providing a more precise estimate
Larger samples reduce sampling variability, leading to narrower confidence intervals and more precise estimates.
What is the relationship between confidence level and interval width?
Answer: Higher confidence levels produce wider intervals
Increasing the confidence level (e.g., from 95% to 99%) requires a wider interval to maintain that higher level of certainty.
What is the margin of error?
Answer: Half the width of the confidence interval, representing maximum expected sampling error
The margin of error represents the maximum expected difference between the sample statistic and the population parameter.
When are confidence intervals more informative than p-values?
Answer: When you need to know the magnitude and direction of an effect, not just significance
Confidence intervals provide both the estimated effect size and its precision, which p-values alone do not convey.
What does it mean if a confidence interval for a difference includes zero?
Answer: The difference is not statistically significant at that confidence level
Including zero means we cannot rule out no difference, so the result is not statistically significant at the given confidence level.