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Confidence Intervals for Means. point estimate – using a single value (or point) to approximate a population parameter. –the sample mean is the best point.

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Presentation on theme: "Confidence Intervals for Means. point estimate – using a single value (or point) to approximate a population parameter. –the sample mean is the best point."— Presentation transcript:

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 t crit =2.093


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