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Unformatted text preview: Chapter 7: Inference on Population Mean(s) Using t Procedures Readings: Chapter 7 September 26, 2009 1 Onesample t Procedures When the population standard deviation is KNOWN , use z procedures: Confidence interval for the population mean : x z * n Hypothesis testing for the population mean ( H : = ): Test statistic z = x / n Both inference procedures are based on the sampling distribution of X : X N ( X = , X = n ) , or equivalently, Z = X / n N (0 , 1) . When the population standard deviation is NOT KNOWN (lecture 6) : Use the sample standard deviation s to estimate Standard error of the sample mean: SE X = s n The sampling distribution of X s/ n is: T = X s/ n t ( n 1) , where t ( n 1) denotes the t distribution with n 1 degrees of freedom . Confidence interval for the population mean : x t * s n Hypothesis testing for the population mean ( H : = ): Test statistic t = x s/ n 1 The tDistribution When the population standard deviation is unknown, T = X s/ n has a tdistribution. There is a different tdistribution for each sample size, so t ( k ) stands for the tdistribution with k degrees of freedom. Degrees of freedom for T = X s/ n is k = n 1. As the degrees of freedom increase, the tdistribution looks more like the normal distribu tion (because as n increases, s ). tdistributions are symmetric about 0 and are bell shaped. They are just a bit wider than the standard normal distribution. To use the ttable (Table D): The ttable is set up differently than the normal table. The uppertail probability on the top of the table refers to the area to the right of the t * values, called the critical value . We start with the desired area and read off the critical values (in the normal table, we started with a z and we read probabilities). Note the confidence level C on the bottom. A 90% confidence level gives the same critical value as the upper tail probability of 0.05 does. What happens if your degrees of freedom are not on the table? Always round DOWN to the next lowest degrees of freedom to be conservative. 2 Example 1 : How accurate are radon detectors of a type sold to homeowners? To answer this question, university researchers placed 12 detectors in a chamber that exposed them to 105 picocuries per liter of radon. The detector readings were as follows: 91.9 97.8 111.4 122.3 105.4 95.0 103.8 99.6 119.3 104.8 101.7 96.6 The sample mean is x = 104 . 13 and the sample standard deviation is s = 9 . 40....
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This note was uploaded on 04/23/2011 for the course STAT 301 taught by Professor Staff during the Spring '08 term at Purdue UniversityWest Lafayette.
 Spring '08
 Staff

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