Podcast
Questions and Answers
What is a categorical variable?
What is a categorical variable?
What defines a quantitative variable?
What defines a quantitative variable?
What is a census?
What is a census?
The result of measuring or counting every individual in a population.
What is a sample?
What is a sample?
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What is meant by population in data collection?
What is meant by population in data collection?
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Bias occurs when all individuals in a population have an equal chance of being selected for a sample.
Bias occurs when all individuals in a population have an equal chance of being selected for a sample.
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What is a convenience sample?
What is a convenience sample?
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What is a voluntary response sample?
What is a voluntary response sample?
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What does randomness mean in sampling?
What does randomness mean in sampling?
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What is a simple random sample (SRS)?
What is a simple random sample (SRS)?
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What is a stratified sample?
What is a stratified sample?
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What is a cluster sample?
What is a cluster sample?
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Study Notes
Data Collection & Sampling Vocabulary
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Categorical variable: Places individuals into specific groups or categories, such as gender or letter grades.
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Quantitative variable: Involves numeric information, which can be measured, such as age, height, or grade levels.
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Census: A comprehensive count or measurement of every individual in a population, providing complete data.
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Sample: A subset of a population chosen for counting or surveying, used to make inferences about the population.
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Population: The entire group of individuals or items that are of interest in research or survey.
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Bias: Arises when certain individuals in a population have a higher probability of being selected for a sample, leading to skewed results.
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Convenience sample: Comprises individuals that are easiest to access or reach, often leading to unrepresentative outcomes.
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Voluntary response sample: Consists solely of volunteers, usually resulting in biased data as these individuals may not represent the overall population.
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Randomness: Ensures that every individual in the population has an equal chance of being selected for the sample, promoting fairness.
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Simple random sample (SRS): A sampling method where every possible sample has an equal probability of selection, ensuring unbiased representation.
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Stratified sample: Divides the population into distinct subgroups (strata) and selects random samples from each strata proportionate to their sizes, enhancing representativeness.
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Cluster sample: Involves dividing the population into clusters and randomly selecting entire clusters for study, including all individuals within those clusters.
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Description
Test your knowledge on key terms related to data collection and sampling. This quiz covers essential vocabulary such as categorical and quantitative variables, population, and sample biases. Perfect for students learning about research methods and statistical sampling.