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Sample Surveys Ch. 12. The Big Ideas 1.Examine a Part of the Whole 2.Randomize 3.It’s the Sample Size.

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Presentation on theme: "Sample Surveys Ch. 12. The Big Ideas 1.Examine a Part of the Whole 2.Randomize 3.It’s the Sample Size."— Presentation transcript:

1 Sample Surveys Ch. 12

2 The Big Ideas 1.Examine a Part of the Whole 2.Randomize 3.It’s the Sample Size

3 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

4 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

5 Methods of Sampling Good Simple Random (SRS) Stratified Random Cluster Multistage Systematic Bad Voluntary Response Convenience

6 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

7 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

8 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

9 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

10 Good Sampling Methods (cont.) Systematic Sampling – Start the sample with a random selection – Select every nth person until you reach your sample size

11 Good Sampling Methods (cont.) Multistage Sampling – A combination of different sampling methods

12 Bias The result of sampling methods that over or under emphasize some characteristic of the population

13 Bias It is very difficult to recover good data once bias is introduced Spend the time/effort/money to ensure an unbiased

14 Randomize Randomizing our selection helps to ensure that on average the sample looks like the population

15 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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