Law of Large Numbers
Definition
A principle in probability theory stating that as more observations are collected, the sample mean will converge to the population mean.
Analogy
Imagine you have a jar filled with jelly beans, some red and some blue. If you keep randomly picking jelly beans from the jar and recording their colors, eventually your average proportion of red jelly beans will get closer and closer to the true proportion in the entire jar.
Related terms
Sampling Distribution: The distribution of sample statistics (e.g., means or proportions) obtained from repeated sampling.
Central Limit Theorem: A theorem stating that as sample size increases, regardless of population shape, the sampling distribution approaches a normal distribution.
Variability: The spread or dispersion of data points around their mean.
"Law of Large Numbers" appears in:
Study guides (2)
Additional resources (1)
Practice Questions (5)
- What is the role of the law of large numbers in statistics?
- What is the purpose of the law of large numbers in statistics?
- What does the law of large numbers state in statistics?
- Which of the following best describes the law of large numbers?
- Which of the following examples demonstrates the application of the law of large numbers?
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