Notes 3 - Chapter 3- Producing Data Some questions to ask...

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Chapter 3- Producing Data Some questions to ask before producing data: What is the group of interest? What information about the group are we interested in? How do we collect this information? 3.1 Design Samples: Population, Sample: The population in a statistical study is the entire group of individuals about which we want information. -Often, it is too time-consuming or expensive to obtain data from the entire population. A sample is a part of the population from which we actually collect information used to draw conclusions about the whole. -We use the sample to draw conclusions about the entire population. -We call this process inference. Example 1: A department store mails customer satisfaction survey to people who make credit purchases at the store. This month, 45,000 people made credit card purchases. Surveys are mailed to 1000 of these people, chosen at random, and 137 people return the survey form. What is the population for this survey? What is the sample from which information was actually obtained? Population: Sample: Example 2: A political scientist wants to know how the college students feel about the Social Security system. She obtains a list of the 2356 undergraduates at her college and mails a questionnaire to 250 students selected at random. Only 104 questionnaires are returned. Population: Sample: Collecting Data: Can we collect information from the entire population easily/quickly/cheaply? If so, perform a census. If not, how should we sample from the population? A Census: The collection of data from every member of a population. The only way to find the true value of a parameter. Often are very impractical, meaning we must use sample.
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Representative Sample: These are samples in members are genera These samples will c Sampling Design: The sampling design is the important to select a sampl of bias to be introduced in t Samples should be as rep A biased sample is one tha response from a biased sam population). It is also important to selec better. Small samples tend acquired from a biased sam population from which that Bad Sampling Metho Sampling badly leads to obt population that it is trying t Bias: The design of a study Bad Sampling Method 1) Convenience Samp very cheap and conv data. in which the relevant characteristics of the sam ally the same as the characteristics of the pop contain little or no bias. e method used to select a sample from a popu le completely randomly so that we do not allo the responses. resentative of the population as possible.
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This note was uploaded on 04/02/2012 for the course STA 2023 taught by Professor Bateh during the Spring '08 term at Florida State College.

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Notes 3 - Chapter 3- Producing Data Some questions to ask...

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