binomial distribution
- noun
- /baɪˈnoʊmiəl dɪstrɪˈbjuːʃən/
- Specialized
- The results of independent trials with dichotomous outcomes can be modeled with a binomial distribution.
- negative binomial distribution
- assume a binomial distribution
- models using the binomial distribution
Examples
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The results of independent trials with dichotomous outcomes can be modeled with a binomial distribution.
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Pre-test values and post-test values were simulated from a binomial distribution.
Academic text (2010) -
In fact, if you were to plot this thing, if you plot the binomial distribution function, it looks something like this.
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You can start to see one here for a mean of five that looks kind of close to the binomial distribution that I showed you earlier.
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Analyses assumed a binomial distribution in which the two possible outcomes were to be either a case-patient or a control.
Academic text (2012) -
The percentage correct scores measured pre-treatment and post-treatment can be considered as coming from two correlated binomial distributions.
Academic text (2010) -
Assuming a normal approximation to the binomial distribution, the 95% confidence interval for the rod and reel mortality rate is 0-9.3%.
Academic text (1998) -
Analyses assumed a binomial distribution in which the two possible outcomes were to be either a case-patient or a control.
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Pre-test values and post-test values were simulated from a binomial distribution.
Synonyms
How numbers spread across a set of results, often shown on a graph
A way to show how often different values occur in data like test scores
Surface Forms
Morphology
The constituents give a clear partial clue: 'binomial' signals a two-term/two-outcome structure and 'distribution' signals a statistical/frequency spread, so a learner could infer this is a distribution related to two categories (e.g., successes/failures). However, the precise technical sense (fixed number of independent trials, same probability of success, counting number of successes) is specialized and not fully predictable from the parts alone, so prior statistical knowledge is needed.
Etymology
Binomial distribution comes from bi- and -nomial: bi- means 'two' and -nomial points to two 'parts', so it names a model for situations with two possible results. Imagine flipping a coin many times — the model shows the chance of getting a certain number of 'successes' (like heads) in a fixed number of tries, which is why it describes counts of 'successes'.