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Unformatted text preview: Testing hypotheses about the population mean Consider the following problem (based on Keller 2006, exercise 9.22 p. 290): You know from past experience that the weight of a can of salmon is a normal random variable with a standard deviation of .18 ounce. The manufacturer claims that the net weight of a can has a mean of 6.05 ounces (or more): 6.05 We focus on the is equal to part of the claim: = 6.05 A claim like this is called the null hypothesis (H ) H : = 6.05 What is the competing claim? .. The competing claim is called the alternative hypothesis: H a : < 6.05 onesided alternative: values of X <<< 6.05 are consistent with H a You draw a random sample of 36 cans and weigh them. The sample mean ( X ) is 5.97 ounces. Is this evidence consistent with H ? Let us first draw the distribution that X would have if = 6.05 If the null hypothesis ( = 6.05) is true, X is normally distributed with: o a mean of x = = 6.05 ounces, and o a standard deviation of x = n = .18 36 = .03 ounce o normal_distribution_area.xls o hence, the probability that the sample mean is 5.97 ounces or less is: [Use normal_distribution_area.xls or TI83: normcdf(low,up,mean,standard deviation) P( X 5.97  = 6.05) = .0038 = .38% Comment on the claim made by the manufacturer. Answer: Given the low probability of finding a sample mean of 5.97 ounces or less, the claim appears to be false. we would tend to reject the claim; Is it possible that we rejected the null hypothesis while it is true ? Yes! Unlikely ( P = .38%), but possible. In that case, rejecting the null hypothesis would be a wrong decision. This decision error (rejecting the null hypothesis when it is true) is called a type I decision error . 1 We just computed the probability of making a type I decision error : P (reject H  H is true) = P (type I error) = pvalue = .38% Decision rule: Reject H only if the probability of making a type I error is sufficiently small. Procedure: o Compute pvalue = P (type I error) = P (reject H  H true) (example: pvalue = .0038 = .38%) o Determine which maximum probability of making a type I error you are willing to tolerate: = significance level Conventionnally, = 5%, but see (*) below! o Decision rule: Reject H 0 if ( pvalue) < (significance level 29 . Report as: "As the pvalue (.38%) is less than the significance level (5%), I can safely reject the null hypothesis that the mean weight is 6.05 ounce, in favor of the alternative hypothesis that it is less than 6.05 ounce." 2 [More details:] Hypotheses A hypothesis is a claim. Example of criminal trial: o Null hypothesis ( H ): defendant is innocent o Alternative hypothesis ( H 1 ): defendant is guilty Jury decides (convict/acquit) on basis of evidence presented at trial....
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This note was uploaded on 08/30/2009 for the course MATHEMATIC m801 taught by Professor Ichigaara during the Spring '09 term at Yaşar Üniversitesi.
 Spring '09
 ichigaara
 Standard Deviation

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