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Understanding Confidence Intervals
A confidence interval estimates the range within which a population parameter is likely to lie, based on sample data. It uses sample mean, standard deviation, and sample size to determine margins of error.
Interpretation Rule
A 95% confidence interval does not mean there is a 95% probability that the true mean lies in the interval. It means that if we repeat the sampling process indefinitely, 95% of the calculated intervals will contain the true population parameter.
Frequently Asked Questions
When should I use a Z-score vs a T-score?
Use Z-scores when the population standard deviation is known and the sample size is large (n > 30). Use T-scores when the population standard deviation is unknown and sample size is small.
