Lecture11_print - Chapter 8: Inference on Proportions...

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Unformatted text preview: Chapter 8: Inference on Proportions Readings: Sections 8.1-8.2 1 Introduction There is NO SPSS work in this chapter. We will do everything by hand. In previous chapters (5, 6, 7) we looked at confidence intervals and hypothesis testing for problems involving means, where we have a quantitative variable. For problems involving counts and proportions, we have a categorical (Which? or Do you? or Yes or no?) variable. Example 1 : a. Did you vote in the last election? The response would be either a Yes or a No. The variable is categorical, the response is the value the variable takes on for each unit/person. If I did a survey of this class, I could accumulate the count of Yes responses and describe this count as a proportion of the total. b. What academic year are you in at Purdue? The response would be either Fresh- man, Sophomore, Junior, or Senior. Again, I could accumulate the count of each and describe each as a proportion of the total. In both cases we are interested in estimating the unknown proportion, p , from a population. The statistic, p (sample proportion) estimates the population parameter p . Population and Sample proportions In statistical sampling we often want to estimate the proportion, p , of successes in a population. Success is when the categorical variable takes on one particular value. We normally call whatever characteristic we are studying a success. Population proportion : p = Count of successes in population Size of population Sample proportion...
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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 University-West Lafayette.

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Lecture11_print - Chapter 8: Inference on Proportions...

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