Workshop11 - CHEN 3010 Applied Data Analysis Names Fall...

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CHEN 3010 Applied Data Analysis Fall 2004 Names: __________________________ Workshop # 11 Hypothesis Testing Background and Supplement on Hypothesis Testing Hypothesis testing is central to applied statistics. It is the formal method used to reach qualified conclusions, such as, “the product from vendor A is of higher quality than the product from vendor B.” There are several concepts related to hypothesis testing that are somewhat confusing and take some getting used to. The purpose of this workshop is to start that “getting used to” process. You will have more practice through your homework assignments. Let’s illustrate the set-up of a hypothesis test with an example from a previous workshop. Let’s say that Boyer’s coffee claims that their coffee bags weigh 40 grams. After taking measurements of about 150 bags, we think that they are shorting us on their coffee, but, given the variability of the weights of the bags, we’re not quite sure. [If the average weight were 35 grams with a range of ± 1 gram, we wouldn’t need statistics!] We propose two hypotheses: H 0 : bag wt = 40 g H 1 : bag wt < 40 g The first of these is called the null hypothesis (H 0 ): the second is called the alternate hypothesis 1 ). We would like to prove the alternate hypothesis and be able to reject the null hypothesis. That is the way it is always set up: test to prove the alternate hypothesis and reject the null hypothesis. Note here that the probability that the null hypothesis is exactly true is virtually zero, since the bag weight is a continuous variable (The only way it could turn out to be true is via the scale that we use to measure the weight, since it is feasible for the scale to show exactly 40.000 g.).
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This note was uploaded on 10/11/2011 for the course CHEN 3010 taught by Professor Kompala,dh during the Spring '08 term at Colorado.

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Workshop11 - CHEN 3010 Applied Data Analysis Names Fall...

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