Probability theory and stochastic processes Definition
Cumulative distribution function
Builds on Random variableProbability distribution
Definition
Let be a real random variable on a probability space . The cumulative distribution function of is the function with More generally, the cumulative distribution function of a probability distribution on is .
Remarks
For , . is nondecreasing and right-continuous, with limit at and limit at . Conversely, each function with these properties is the cumulative distribution function of some distribution. The jump of at is . For a fair die, for , for , and for .
Reading path
To understand this page from the ground up, read these 40 pages in order. The foundations come first.
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- no evidence level
- Construction of the reals from Cauchy sequences concept
- Element definition
- Integers object
- Ordered field definition
- Proposition concept
- Random experiment concept
- Rational numbers object
- Real numbers object
- Set definition
- Ring of integers statement
- Disjunction definition
- Implication definition
- Predicate definition
- Ordered pair definition
- Union definition
- Sample space definition
- The rationals form a field statement
- Existential quantifier definition
- Universal quantifier definition
- Cartesian product definition
- Subset definition
- The rationals form an ordered field statement
- Uniqueness quantifier definition
- Binary relation definition
- Universal set definition
- Order on the reals definition
- Power set definition
- Complement definition
- Function definition
- Interval definition
- Preimage of a set definition
- Sigma-algebra definition
- Event definition
- Borel sigma-algebra definition
- Probability axioms concept
- Probability measure definition
- Probability distribution definition
- Probability space definition
- Random variable definition
- Cumulative distribution function definition
Where this leads
137 pages build on this one.
- Chernoff bound
- Law of the unconscious statistician
- Density of the normal distribution
- Exponential distribution
- Characteristic function of a sum of independent random variables
- Variance of the normal distribution
- Probability density function
- Likelihood function
- Poisson point process
- Gamma distribution
- De Moivre–Laplace theorem
- Convolution of probability distributions
- Normal distribution
- Median
- Method of moments
- Mean of the normal distribution
- Moment-generating function of the normal distribution
- Quantile function
- Uncorrelated random variables that are not independent
- Kurtosis
- Mean of the geometric distribution
- Neyman–Pearson lemma
- P-value
- Chi-squared test
- Convergence in probability implies convergence in distribution
- Central limit theorem
- 68–95–99.7 rule
- Lévy's continuity theorem
- Convergence of random variables
- Maximum likelihood estimation
- Multivariate normal distribution
- Skewness
- Student's t-test
- Convergence in distribution
- The cumulative distribution function determines the distribution
- Bayesian inference
- Confidence interval
- Coupon collector's problem
- Characteristic function
- Cauchy distribution
- Moment-generating function
- Student's t-distribution
- Characteristic function of the normal distribution
- Sum of independent normal random variables
- Moment
- Beta distribution
- Cumulant generating function
- Chi-squared distribution
- Limit of the cumulative distribution function at infinity
- Moments are derivatives of the moment-generating function at zero
- The characteristic function determines the distribution
- Continuous uniform distribution
- Hoeffding's inequality
- Moment-generating function of a sum of independent random variables
- Monotonicity of the cumulative distribution function
- Poisson limit theorem
- Tail sum formula for expectation
- Conditional probability distribution
- Memorylessness
- Central moment
- Bernstein–von Mises theorem
- Poisson regression
- Koksma–Hlawka inequality
- Hodges' superefficient estimator
- Cramér–Wold theorem
- Boolean model
- Wald–Wolfowitz optimality of the sequential probability ratio test
- Consistency of the maximum likelihood estimator
- Bayes factor
- Pickands–Balkema–De Haan theorem
- Contiguity of measures
- Lindley's paradox
- M-estimator
- Score test
- McDiarmid's inequality
- Asymptotic normality of the maximum likelihood estimator
- Mann–Whitney U test
- Score
- F-distribution
- Edgeworth expansion
- Monotone likelihood ratio
- Whittle likelihood
- Logistic regression
- Cramér–von Mises criterion
- Azuma's inequality
- Kernel density estimation
- Erdős–Kac theorem
- Continuous mapping theorem
- Monte Carlo integration
- Breakdown point
- Delta method
- Noncentral chi-squared distribution
- Hájek–Le Cam convolution theorem
- Behrens–Fisher problem
- Hodges–Lehmann estimator
- Kruskal–Wallis test
- Information geometry
- Wishart distribution
- Sign test
- Slutsky's theorem
- Empirical likelihood
- Dvoretzky–Kiefer–Wolfowitz inequality
- Bayesian information criterion
- Berry–Esseen theorem
- Cochran's theorem
- Quantile regression
- Akaike information criterion
- Credible interval
- Independence of sample mean and sample variance for normal samples
- Estimating equations
- Anderson–Darling test
- Spearman's rank correlation coefficient
- Generalized method of moments
- Bernstein inequalities
- Empirical distribution function
- Moments of the log-normal distribution
- Missing data mechanisms
- Likelihood-ratio test
- Conjugate prior
- Kolmogorov–Smirnov test
- Expectation–maximization algorithm
- Hotelling's T-squared distribution
- Wald test
- Generalized linear model
- Box–Jenkins method
- Binomial proportion confidence interval
- False discovery rate and the Benjamini–Hochberg procedure
- Neyman construction
- Wilks' theorem
- Permutation test
- Fisher's exact test
- Bonferroni correction
- Local asymptotic normality
- Frequentist inference
- Likelihood principle
- Observed information
- Point estimation
Further reading
About this page
| Tag | 0MXMS3AE13 |
|---|---|
| URI | m2://0MXMS3AE13 |
| Kind | definition |
| Writing | W1 stated |
| MSC | 60E05 |
| Defines | Cumulative distribution function |
| Uses | Random variable, Probability distribution |
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What links here
Used by
- Probability density function
- Median
- Quantile function
- Convergence in probability implies convergence in distribution
- Convergence in distribution
- The cumulative distribution function determines the distribution
- Limit of the cumulative distribution function at infinity
- The characteristic function determines the distribution
- Monotonicity of the cumulative distribution function
- Tail sum formula for expectation
- Pickands–Balkema–De Haan theorem
- Mann–Whitney U test
- Cramér–von Mises criterion
- Dvoretzky–Kiefer–Wolfowitz inequality
- Anderson–Darling test
- Spearman's rank correlation coefficient
- Empirical distribution function
- Kolmogorov–Smirnov test