Chapter_8

# Chapter_8 - STAT 2053 Elementary Statistics Chapters 8...

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STAT 2053 – Elementary Statistics Chapters 8 – Producing Data: Sampling 1

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Collecting Data The manner in which we acquire and produce data is very important in terms of getting sound answers to our questions. This chapter focuses on the do’s and don’ts of collecting data in order to reach the correct conclusions when it comes time to analyze the data. 2
Population and Sample Definitions : In a statistical study: The population is the entire group of individuals about which we want information. Researchers often want to answer questions about some large group of individuals (this group is called the population ) Populations are described as generally as possible. 3

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Population and Sample Definitions : In a statistical study: A sample is a part of the population from which we actually collect information. Often the researchers cannot measure (or survey) all individuals in the population, so they measure a subset of individuals that is chosen to represent the entire population (this subset is called a sample ) 4
Population and Sample Definitions : In a statistical study: A sampling design describes exactly how to choose a sample from the population. The researchers then use statistical techniques to make conclusions about the population based on the sample 5

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Sampling Example : Physical Plant wants to know how college students feel about the availability of parking. A survey is sent to 250 of the 25,000 students at OSU, chosen randomly. Physical Plant receives 104 responses. What are the population and sample of this study? Population – Sample – 6
Sampling We depend on samples because, often, it is either impossible or inconvenient to contact every individual in a population. The procedure for planning a sample: 1. Define the population you’re interested in. 2. Define exactly what you want to measure (variables) 3. Prepare a sampling design 7

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Bad Sampling Designs Definition : A sampling design is biased if it systematically favors certain outcomes. Biased sampling designs will produce results that do not truly reflect the entire population. It’s like asking a bunch of barbers if you need a haircut. You have a good idea of the answer before you ask. 8
9 Bad Sampling Designs 1. Convenience sampling selecting individuals that are easiest to reach 1. Voluntary response sampling allowing individuals to choose to be in the sample Both of these techniques are biased systematically favor certain outcomes

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Two sample designs that are typically biased : 1)A convenience sample is a sample that’s selected by taking the members of the population that are the easiest to reach. Example : If I wanted information about the political parties of college students, and I easily stepped outside my office door onto campus to take a sample of OSU students, why is this biased? 10
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## This note was uploaded on 09/23/2011 for the course STAT 2053 taught by Professor Staff during the Fall '08 term at Oklahoma State.

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Chapter_8 - STAT 2053 Elementary Statistics Chapters 8...

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