Sampling

Question 1

What is sampling?

Answer 1

The process of selecting observations in research is called sampling.

Question 2

Why do we need sampling?

Answer 2

• Population is too large to recruit (e.g Canadian population)
• Population is too dispersed or difficult to contact
• To get results quickly – (ex. opinion polls)

Key to sampling – get a “Representative Sample”

Question 3

Sampling

Answer 3

• Sample is a special subset of a population that is observed for purposes of making inferences about the nature of the total population itself
• Sampling is the process of selecting observations

There are two major types of sampling:
• probability and non-probability sampling

Question 4

Probability Sampling

Answer 4

Probability sampling techniques, involve random sampling
• Specific sampling techniques can allow us to determine or control the likelihood of specific individuals being selected for the study
• Even though, probability sampling is quite precise, it is not always possible to use probability sampling techniques

Question 5

Non-Probability Sampling

Answer 5

Non-probability sampling, which does not have random selection

Question 6

Main Types of Non-Probability Sampling

Answer 6

• Quota sampling
• Reliance on available subjects
• Purposive/judgmental sampling
• Snowball sampling

Question 7

Main Types of Non-Probability Sampling - Quota Sampling

Answer 7

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Question 8

Main Types of Non-Probability Sampling - Reliance on Available Subjects

Answer 8

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Question 9

Main Types of Non-Probability Sampling - Purposive/Judgemental Sampling

Answer 9

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Question 10

Main Types of Non-Probability Sampling - Snowball Sampling

Answer 10

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Question 11

Probability Sampling

Answer 11

• The main logic of probability sampling is to improve representation of its population if all members of that population have an equal chance of being selected in the sample.
• It tries to make the sample as more approximate as possible to the general population.

Question 12

Main Rules of Probability Sampling

Answer 12

• Larger the sample, the more confidence we have in the sample’s representativeness.
• Representative sampling and random sampling are two techniques used to help ensure data is free of bias.

Question 13

Main Types of Probability Sampling

Answer 13

• Simple random sampling
• Systematic random sampling
• Stratified sampling
• Cluster sampling

Question 14

Main Types of Probability Sampling - Simple Random Sampling

Answer 14

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Question 15

Main Types of Probability Sampling - Systematic Random Sampling

Answer 15

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Question 16

Main Types of Probability Sampling - Stratified Sampling

Answer 16

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Question 17

Main Types of Probability Sampling - Cluster Sampling

Answer 17

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