Glossary of Statistical Terms: Definition Central limit theorem
The central limit theorem is a rule (more precisely a theorem), which helps us to calculate the distribution of central values of different samples from a population. The theorem states that the distribution of central values in a sample approximates a normal distribution with an increasing sample size. It does not matter, however, how the measured values are distributed in the population.
The central limit theorem (CLT) allows us to make statements on the deviations of a central value in a sample, without taking into consideration the central values of other samples.
Please note that the definitions in our statistics encyclopedia are simplified explanations of terms. Our goal is to make the definitions accessible for a broad audience; thus it is possible that some definitions do not adhere entirely to scientific standards.
- Central limit theoremCentral limit theorem
- Cluster analysisCluster analysis
- Cluster sampleCluster sample
- Coefficient of correlationCoefficient of correlation
- Competitor analysisCompetitor analysis
- Conditional probabilityConditional probability
- Confidence levelConfidence level
- Conjoint analysisConjoint analysis
- Cross-sectional dataCross-sectional data