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Published byReynard Foster Modified over 9 years ago
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Sample Surveys Ch. 12
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The Big Ideas 1.Examine a Part of the Whole 2.Randomize 3.It’s the Sample Size
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Examine a Part of the Whole Population -- the entire group of individuals that we want information about Sample -- a part of the population that we actually examine in order to gather information
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Sampling vs. Census Sampling Studies a part to gain information about the whole Powerful (when done correctly) Census Attempts to gather information from every member of the population Difficult Time consuming Expensive (Sometimes) Impossible
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Methods of Sampling Good Simple Random (SRS) Stratified Random Cluster Multistage Systematic Bad Voluntary Response Convenience
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Bad Sampling Methods Voluntary Response Sample – A large group is invited to respond and all who respond are counted – Internet polls, radio call in polls, etc. – Skewed toward extreme opinions Convenience Sample – Only include individuals who are convenient to sample – Lazy
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Good Sampling Methods Simple Random Samples (SRS) – Every individual has equal chance of being selected, every subgroup (of the desired sample size) has equal chance of being selected
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Good Sampling Methods (cont.) Stratified Random Sample – Divide the population into groups (strata) that are similar in some way – Choose a SRS in each stratum – Combine the SRSs from each strata to form the full sample
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Good Sampling Methods (cont.) Cluster Sample – Divide population into groups (aka clusters) – Randomly select clusters – All individuals in the chosen clusters are selected for the sample
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Good Sampling Methods (cont.) Systematic Sampling – Start the sample with a random selection – Select every nth person until you reach your sample size
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Good Sampling Methods (cont.) Multistage Sampling – A combination of different sampling methods
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Bias The result of sampling methods that over or under emphasize some characteristic of the population
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Bias It is very difficult to recover good data once bias is introduced Spend the time/effort/money to ensure an unbiased
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Randomize Randomizing our selection helps to ensure that on average the sample looks like the population
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Types of Bias Voluntary Response Bias – Survey participants self-select to be included in the survey Nonresponse Bias – Not everyone chosen for the survey responds Response Bias – Anything in the design that influences the responses
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