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1) For a two-sided 95% confidence level, the z critical value is about ±1.96.
2) When \( \sigma \) is unknown and \( n \) is small, it’s fine to plug in \( s \) and still use a z-interval.
3) In a z-interval, the standard error is \( \sigma/\sqrt{n} \).
4) Increasing the sample size \( n \) increases the margin of error for a fixed confidence level.
5) For a one-sided 95% bound, the z critical is about 1.645.
6) The z-test does not require independence of observations.
7) The z-statistic uses degrees of freedom \( n-1 \).
8) A 99% z-interval is typically narrower than a 95% interval for the same data.
9) The Central Limit Theorem guarantees exact normality of the sample mean for any sample size.
10) For a two-sided 90% confidence level, the z critical value is about ±1.645.