Podcast
Questions and Answers
What is the difference between probability and non-probability sampling?
What is the difference between probability and non-probability sampling?
Non-probability sampling does not involve random selection, while probability sampling does. Non-probability samples cannot rely on probability theory, making it difficult to estimate how well the sample represents the population.
Which of the following are types of non-probability sampling methods? (Select all that apply)
Which of the following are types of non-probability sampling methods? (Select all that apply)
- Accidental Sampling (correct)
- Simple Random Sampling
- Purposive Sampling (correct)
- Systematic Sampling
Define Accidental, Haphazard, or Convenience Sampling.
Define Accidental, Haphazard, or Convenience Sampling.
This type of sampling is based on obtaining a sample of people who are conveniently available, such as through television interviews or volunteers.
What is Purposive Sampling?
What is Purposive Sampling?
Which of the following are types of purposive sampling? (Select all that apply)
Which of the following are types of purposive sampling? (Select all that apply)
What is Modal Instance Sampling?
What is Modal Instance Sampling?
What involves Expert Sampling?
What involves Expert Sampling?
In quota sampling, you select people ______.
In quota sampling, you select people ______.
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Study Notes
Non-Probability Sampling Overview
- Non-probability sampling lacks random selection, making representation of the population uncertain.
- Probability sampling allows estimation of confidence intervals and better represents the population.
- Researchers prefer probability sampling for accuracy, although non-probability methods may be necessary in certain situations.
Types of Non-Probability Sampling Methods
- Two primary methods: Accidental (Convenience) Sampling and Purposive Sampling.
- Purposive sampling aligns with specific objectives, addressing the sampling problem with a targeted plan.
Accidental, Haphazard or Convenience Sampling
- Commonly used in informal surveys, like television polls, to gauge public opinion quickly.
- Involves sampling available clients or asking for volunteers, lacking evidence of representativeness.
- Generalizations from such samples should be made cautiously due to potential bias.
Purposive Sampling
- Involves selecting a sample with specific intent and predefined groups in mind.
- Example: Interviewing specific demographics like Caucasian females aged 30-40 in public spaces.
- Provides access to targeted opinions but may skew results towards more accessible subgroups.
- Effective for studying cases outside regular patterns of behavior and attitudes.
Types of Purposive Sampling
- Modal Instance Sampling
- Expert Sampling
- Quota Sampling
- Heterogeneity Sampling
- Snowball Sampling
Modal Instance Sampling
- Focuses on the "typical" or modal case in a population, such as the average voter in polls.
- Challenges include defining what constitutes a modal case accurately, particularly in skewed distributions.
Expert Sampling
- Involves selecting individuals with recognized expertise in a specific area.
- Used to validate other sampling approaches, like modal instance sampling.
- Experts can still make mistakes, emphasizing the need for critical assessment of their insights.
Quota Sampling
- Participants are selected based on specific characteristics to meet predetermined quotas.
- Non-random selection may lead to bias, as the sample may not accurately reflect the broader population.
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