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Confidence Intervals for Means

Confidence Intervals for Means. point estimate – using a single value (or point) to approximate a population parameter. the sample mean is the best point estimate of the population mean  The problem is, with just one point, how do we know how good that estimate is?

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Confidence Intervals for Means

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  1. Confidence Intervals for Means

  2. point estimate – using a single value (or point) to approximate a population parameter. • the sample mean is the best point estimate of the population mean  • The problem is, with just one point, how do we know how good that estimate is? • A confidence interval (or interval estimate) is a range of interval of values that is likely to contain the true value of the population parameter. • confidence interval = estimate  margin of error • common choices are: • 90% ( = 0.10); • 95% ( = 0.05); • 99% ( = 0.01).

  3. When sample sizes are small, we must use the t-distribution instead of the normal curve (z-distribution). (Appendix C – p477) • This table relies on ‘degrees of freedom’, which is always n – 1.

  4. Create a 95% confidence interval for the starting salaries of 20 college graduates who have taken a statistics course if the mean salary is $43,704, and the standard deviation is $9879. • margin of error s = standard deviation = $9879 n = sample size = 20 df= degrees of freedom = n-1=19 tcrit=2.093

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