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Lecture 13

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Health Sciences
Margaret Schneider

HE 201 Lecture 13 Oct 11, 2013 Sampling  The process of choosing members of a population to be included in a sample  Research uses data from a sample to make inferences about a population Selecting a Research Sample: Ex. How do undergraduate student spend their free time?  Is it going to be a specific university? People representation of different programs Which year are they in their undergrad Need an operational definition of free time Gender, age, department How do you select sample What is your desired sample and who to you want to generalize your results to? Population  The defined group of individuals from which a sample is drawn  Sample should closely represent population Generalizability Goal: generalize results from the limited setting in which they were originally obtained to a larger population When results are generalizable, they can be applied to different populations in different settings Selection  How do we ensure that the sample selected is representative of the pop in which we’re interested?  If you select sample effectively, your results will be generalizable  You are trying to create a “mini population”. Two major types of Sampling Probability Sampling  The likelihood of any one member of pop being selected is known I.e. 8000 wlu students, sample 200, probability is 0.025 Nonprobability Sampling  Likelihood of selecting any one member of the pop is not known I.e., telephone book sampling  not good, because not everyone is not in the phonebook (people will be left out of sampling) Probability Sampling Strategies Simple Random Sampling:  Each member of the pop has an equal and independent chance of being selected as part of the sample Equal- no bias that one person will be chosen over another Independent- choice of one person will not affect the choice of another Steps in Simple Random Sampling  Define the pop from which you want to select the sample  List all members of pop  Assign numbers to each member of pop  Use a criterion to select the same you want (e.g. every even number) Types of Simple Random Sampling  Use table of random numbers  Use a computer to generate random numbers Systematic Random Sampling  Divide the size of pop by size of desired sample E.g. pop is 50, sample is 10, then select every 5 name  Choose one name from list at random and select every 5 name from there (Systematic aspect of it takes away the equality of being chosen. However, it is still random) Stratified Sampling  Assure that the profile of the same matches the profile of pop  Similar to simple random sampling but pop is now divided in to groups on the basis of the variables of interest E.g. WLU has 65% females and 35% males, want sample of 100, therefore select 65 females and 35 males randomly from the two
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