Questions and Answers
Define random sampling.
The process of using chance to select individuals from a population to be included in the sample.
For the results of a survey to be reliable, what must the characteristics of the individuals in the sample consist of?
Must be representative of the characteristics of the individuals in the population.
What is the key to obtaining a sample representative of a population?
Let chance or randomness play a role in dictating which individuals are in the sample.
What happens if convenience is used to obtain a sample?
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What are the four basic sampling techniques?
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What is the most basic sample survey design?
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What is simple random sampling like?
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What is the definition of a simple random sample?
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Is the number of individuals in the sample always less than the number of individuals in the population?
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What does the word sample refer to?
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What is a frame?
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How do you select the individuals in a simple random sample?
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What does N represent when selecting the individuals in a simple random sample?
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What does n represent?
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What do you need in order to number the individuals in the population?
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What happens to an individual in a sample without replacement?
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What happens to an individual in a sample with replacement?
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What is a seed?
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Study Notes
Random Sampling Basics
- Random sampling is a method used to select individuals from a population using chance, ensuring all members have an equal opportunity to be chosen.
- For survey results to be trustworthy, the sample characteristics must reflect those of the broader population.
Importance of Chance in Sampling
- A sample needs randomness to be representative; using convenience leads to biased results and meaningless data.
- Simple random sampling is the foundational technique for gathering unbiased samples.
Sampling Techniques
- Four primary sampling techniques:
- Simple random sampling
- Stratified sampling
- Systematic sampling
- Cluster sampling
Characteristics of Simple Random Sampling
- Simple random sampling can be likened to drawing names from a hat.
- In this method, each potential sample size has an equal probability of selection.
- Sample size (n) is always less than the population size (N).
Sample and Frame Definitions
- A sample consists of individuals selected to represent the larger population.
- A frame is a comprehensive list of all individuals in the population, essential for creating a sample.
Selection Process
- Individuals in a simple random sample are assigned unique numbers, enabling random selection.
- N denotes the population size, while n indicates the sample size needed for study.
Replacement in Sampling
- In sampling without replacement, selected individuals are removed from the population and cannot be chosen again.
- In sampling with replacement, selected individuals remain in the population, allowing for potential re-selection.
Additional Concepts
- A seed is the initial point used by random number generators to ensure variability in selection.
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Test your knowledge on simple random sampling with these flashcards. Understand the concept, characteristics, and importance of representative samples in survey reliability. Perfect for students studying basic statistics!