Sampling

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# Sampling - PowerPoint PPT Presentation

Sampling. Census and Sample (defined). A census is based on every member of the population of interest in a research project A sample is a subset of the population. Characteristics of a Sample. Representative of the larger population Can be more efficient in terms of cost, time

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## PowerPoint Slideshow about 'Sampling' - avian

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### Sampling

Census and Sample (defined)
• A census is based on every member of the population of interest in a research project
• A sample is a subset of the population
Characteristics of a Sample
• Representative of the larger population
• Can be more efficient in terms of cost, time
• Generalizable results
• Can reflect animate or inanimate populations
The Sampling Frame
• The list of elements from which a sample may be drawn
• Defines the criteria on which elements will be selected
• But, does not ensure that some elements will not be excluded or accurately represented
• Sample frame error
Sampling Unit
• A single element or group of elements subject to selection in a sample
• Ex. An 18 to 24 year old male with senior academic classification
• Ex. Grocery retailers that gross \$30,000 in revenues monthly
Sampling Methods

Probability sampling

• Elements each have a known, calculable non-zero probability of inclusion
• The probability of inclusion is predictable across elements
Sampling Methods

Non-probability sample

• Sampling does not ensure a representative range of elements found in the larger population
Forms of Probability Sampling
• Simple random sampling
• Each member of the population has a known, equal chance of being selected
• Allows comparable estimates without surveying the entire population
Forms of Probability Sampling
• Systematic random sampling
• Sampling occurs based on a skip interval system where every nth member is selected from the population
• Each element at the skip level is selected and interviewed
Systematic Random Sampling
• Directory of Physicians in the Gainesville, FL area
Forms of Probability Sampling
• Stratified random sampling
• Sampling based on applying weights to population stratas
• Proportionate vs. disproportionate stratums
• Appropriate when the population is non-homogenous or has wide variations
Stratified Random Sampling

Proportionate to their representation in the population

65%

23%

12%

Stratified Random Sampling

Disproportionate to their representation in the population

33%

34%

33%

Cluster Sampling
• Segmenting the population to sample based on geography
• Postal codes, electoral constituencies, states, regions
Multi-stage Sampling
• Two-step process
• Select a primary sample based on a pre-specified sampling method
• 35 – 45 YO Women
• Then, selecting a secondary sub-sample from within the larger sample group
• 35 – 45 YO Women who actively invest in the stock market
Forms of Non-probability Sampling
• Convenience sampling
• Participants are selected based on convenience and accessibility
• Quick, uncomplicated, low in cost
• Useful for exploratory research or quick info
Forms of Non-probability Sampling
• Judgment sampling
• Participants are selected based on an expert’s judgment of the characteristics of a representative sample
• Example: the “typical” customer
Forms of Non-probability Sampling
• Quota sampling
• Attempts to ensure demographic characteristics of interest are represented in the sample proportionately to their representation in the population
• Sample based on population percentiles
Forms of Non-probability Sampling
• Snowball sampling
• Initial respondents are selected by probability sampling techniques
• Additional respondents are obtained by referral from initial respondents