Order on the reals
Builds on Construction of the reals from Cauchy sequencesThe rationals form an ordered field
Definition
Construct the real numbers as classes of Cauchy sequences of rational numbers, as in the construction from Cauchy sequences. Let and be real numbers, represented by the Cauchy sequences and of rational numbers. The notation means that there are a rational number and a natural number such that for each . The notation means that or .
Remarks
The relation does not depend on the choice of the sequences that represent and . For all real numbers and , exactly one of , and holds. Thus is a total order. On the rational numbers, this order agrees with the order of the rationals. With Dedekind cuts, the order is inclusion of the lower sets of the cuts.
Reading path
To understand this page from the ground up, read these 8 pages in order. The foundations come first.
Show the path as a graph
- no evidence level
- Construction of the reals from Cauchy sequences concept
- Integers object
- Ordered field definition
- Rational numbers object
- Ring of integers statement
- The rationals form a field statement
- The rationals form an ordered field statement
- Order on the reals definition
Where this leads
415 pages build on this one.
- Variance
- Prior probability
- Absolute value
- Chernoff bound
- Chapman–Kolmogorov equation
- Bias of an estimator
- Identically distributed random variables
- Law of the unconscious statistician
- Density of the normal distribution
- Exponential distribution
- Covariance matrix
- Chebyshev's inequality
- Characteristic function of a sum of independent random variables
- Stationary distribution
- Bernoulli process
- Markov chain
- Statistic
- Law of total variance
- Variance of the normal distribution
- Triangle inequality
- Cauchy–Schwarz inequality for expectations
- Monotonicity of probability
- Every real number has a decimal expansion
- Correlation coefficient
- Variance under translation
- Density of the irrationals
- Almost sure convergence
- Law of total expectation
- Probability density function
- Expectation of a product of independent random variables
- Likelihood function
- Markov's inequality
- Standard score
- Poisson point process
- Gamma distribution
- De Moivre–Laplace theorem
- Buffon's needle problem
- Kolmogorov's zero–one law
- Independent random variables are uncorrelated
- Convolution of probability distributions
- Normal distribution
- Mean of the Poisson distribution
- Statistical hypothesis test
- Independence means the joint law is the product of the marginals
- Median
- Geometric probability
- Intermediate value theorem for connected spaces
- Dirac measure
- Method of moments
- Mean of the normal distribution
- Independent sigma-algebras
- The reals are Archimedean
- Independent and identically distributed random variables
- Classical definition of probability
- Pairwise independent events that are not mutually independent
- Ceiling function
- Marginal distribution
- Moment-generating function of the normal distribution
- Quantile function
- Connected subsets of the real line are intervals
- Weak law of large numbers
- Multiplication rule
- Borel sigma-algebra
- Addition rule for two events
- Random walk
- Random variable with a density
- Uncorrelated random variables that are not independent
- Reverse triangle inequality
- Kurtosis
- Martingale
- Variance of a sum
- Mean of the geometric distribution
- Expected value
- Strong law of large numbers
- Covariance
- Random variable
- Base rate fallacy
- Law of total probability
- Independence of two random variables
- Neyman–Pearson lemma
- Convergence in probability
- Boole's inequality
- P-value
- Chi-squared test
- Convergence in probability implies convergence in distribution
- Central limit theorem
- 68–95–99.7 rule
- Transition matrix
- Conditional variance
- Conditional probability
- Lévy's continuity theorem
- Convergence of random variables
- Maximum likelihood estimation
- Multivariate normal distribution
- Mutual independence of events
- Absolute value is multiplicative
- Skewness
- Galton–Watson process
- Markov property
- Student's t-test
- Discrete random variable
- Bernoulli distribution
- Convergence in distribution
- The cumulative distribution function determines the distribution
- Sample variance
- Bayesian inference
- Confidence interval
- Posterior probability
- Variance under scaling
- Discrete uniform distribution
- Coupon collector's problem
- Cumulative distribution function
- Characteristic function
- Pairwise independence
- Cauchy distribution
- Bayes' theorem
- Variance as the mean of the square minus the square of the mean
- Birthday problem
- Moment-generating function
- Student's t-distribution
- Characteristic function of the normal distribution
- Second Borel–Cantelli lemma
- Sum of independent normal random variables
- Independence of two events
- Linearity of expectation
- Monty Hall problem
- Moment
- Beta distribution
- Probability of the complement
- Expectation with respect to the binomial distribution
- Cumulant generating function
- Joint probability distribution
- Probability distribution
- Stochastic process
- Sample mean
- The reals form an ordered field
- Type I and type II errors
- Almost surely
- Characterization of the floor
- Generating function of a sum of independent random variables
- Chi-squared distribution
- Limit of the cumulative distribution function at infinity
- Hypergeometric distribution
- Moments are derivatives of the moment-generating function at zero
- Density of the rationals
- Almost sure convergence implies convergence in probability
- Bertrand paradox
- First Borel–Cantelli lemma
- The characteristic function determines the distribution
- Interval
- Law of a random variable
- Convergence in mean
- Estimator
- Variance of a sum of independent random variables
- Mean squared error
- Poisson distribution
- Probability measure
- Binomial distribution
- Standard deviation
- Law of total probability for an event and its complement
- Probability mass function
- Gambler's ruin
- Continuous uniform distribution
- There is a natural number n with 1/n below any positive epsilon
- Hoeffding's inequality
- Moment-generating function of a sum of independent random variables
- Continuity of probability measures
- Independence of random variables
- Geometric distribution
- Monotonicity of the cumulative distribution function
- Consistent estimator
- Poisson limit theorem
- Negative binomial distribution
- Tail sum formula for expectation
- Conditional expectation
- Absorbing Markov chain
- Sum of independent Poisson random variables
- Conditional probability distribution
- Floor function
- Probability-generating function
- Memorylessness
- Conditional independence
- Path-connected spaces are connected
- Central moment
- Law of large numbers
- Probability space
- Doob's upcrossing inequality
- Bernstein–von Mises theorem
- Cramér–Rao bound
- Efficiency of an estimator
- Log-rank test
- Functional data analysis
- Poisson regression
- Sequential analysis
- Ergodic decomposition
- Koksma–Hlawka inequality
- Hodges' superefficient estimator
- Martingale representation theorem
- Absorbing set
- Mathematical statistics
- F-test
- Laplace transform of the Dirac delta
- Stationary process
- Orthogonal polynomials on the unit circle
- Cramér–Wold theorem
- Boolean model
- Stochastic partial differential equation
- Wald–Wolfowitz optimality of the sequential probability ratio test
- Doob's martingale inequality
- Seminorm
- Sequential probability ratio test
- Brownian bridge
- Consistency of the maximum likelihood estimator
- Wiener process
- Empirical Bayes method
- Karhunen–Loève theorem
- Brent's method
- Itô isometry
- Absolute continuity
- Bayes factor
- Pickands–Balkema–De Haan theorem
- Basu's theorem
- Variogram
- Robbins–Monro algorithm
- Contiguity of measures
- Order statistic
- Balanced set
- Dirichlet process
- Lindley's paradox
- Universally measurable set
- M-estimator
- Ornstein–Uhlenbeck process
- Kernel regression
- Bayes estimator
- Bisection method
- Adapted process
- Score test
- Kingman's subadditive ergodic theorem
- Multivariate analysis of variance
- McDiarmid's inequality
- Lévy's characterization of Brownian motion
- Asymptotic normality of the maximum likelihood estimator
- Mann–Whitney U test
- Kolmogorov automorphism
- Score
- F-distribution
- Edgeworth expansion
- Crofton formula
- Monotone likelihood ratio
- Sample mean and sample covariance
- Wilcoxon signed-rank test
- Metropolis–Hastings algorithm
- Subderivative
- Continuous-time Markov chain
- Darboux function
- Kriging
- Log-convexity of the gamma function
- Identifiability
- Baire function
- Minimal sufficient statistic
- Whittle likelihood
- Logistic regression
- Convergence to equilibrium of ergodic Markov chains
- Cramér–von Mises criterion
- Azuma's inequality
- Gaussian free field
- Parry measure
- Kernel density estimation
- Erdős–Kac theorem
- Detailed balance
- Coupling from the past
- Robust statistics
- Hidden Markov model
- Finite-dimensional distributions
- Continuous mapping theorem
- Bias–variance decomposition
- Lévy process
- Wald's equation
- Random ordinary differential equation
- Monte Carlo integration
- Time series
- Optional stopping theorem
- Measurable space
- Breakdown point
- Delta method
- Minimum description length
- Noncentral chi-squared distribution
- Hájek–Le Cam convolution theorem
- Logarithmically convex function
- Harmonic measure
- Behrens–Fisher problem
- Submartingale
- Hodges–Lehmann estimator
- Kruskal–Wallis test
- Stochastic difference equation
- Sampling distribution
- Information geometry
- Recurrence and transience of states
- Malliavin calculus
- Wishart distribution
- Birth–death process
- Karamata's inequality
- Bayes risk
- Statistical inference
- Minimum-variance unbiased estimator
- Sign test
- Slutsky's theorem
- Tanaka's formula
- Geometric Brownian motion
- Empirical likelihood
- Dvoretzky–Kiefer–Wolfowitz inequality
- Bayesian information criterion
- Berry–Esseen theorem
- Continuity of measure from below and above
- Legendre transformation
- Hunt process
- Cochran's theorem
- Stochastic approximation
- Jackknife
- Quantile regression
- Markov chain mixing time
- Birkhoff's ergodic theorem
- Akaike information criterion
- Hewitt–Savage zero–one law
- Jensen's inequality for integrals
- Statistical model
- Bramble–Hilbert lemma
- Reflection principle
- Credible interval
- Conformal modulus
- Independence of sample mean and sample variance for normal samples
- Self-similar process
- Gibbs sampling
- Estimating equations
- Supermartingale
- Anderson–Darling test
- Spearman's rank correlation coefficient
- Family-wise error rate
- Markov chain Monte Carlo
- Nested intervals theorem
- Dickey–Fuller test
- Generalized method of moments
- Doob's martingale convergence theorems
- Random integral equation
- Uniformly most powerful test
- Bernstein inequalities
- Kendall rank correlation coefficient
- Semimartingale
- Empirical distribution function
- Bootstrap
- Minimax approximation
- Influence function
- Oseledets theorem
- Itô calculus
- Ancillary statistic
- Stopped process
- Jeffreys prior
- Moments of the log-normal distribution
- Complete statistic
- Horvitz–Thompson estimator
- U-statistic
- Fractional Brownian motion
- Bayesian hierarchical model
- L-estimator
- Power of a test
- Parametric model
- Randomization
- Sufficient statistic
- Gaussian process
- Missing data mechanisms
- Likelihood-ratio test
- Karlin–Rubin theorem
- Conjugate prior
- Kolmogorov–Smirnov test
- Expectation–maximization algorithm
- Hotelling's T-squared distribution
- Burkholder–Davis–Gundy inequality
- Doob–Meyer decomposition theorem
- Cross-validation
- Barbier's theorem
- Wald test
- Extremal length
- Pivotal quantity
- Generalized linear model
- Random graph
- Tame Fréchet space
- Box–Jenkins method
- Kolmogorov continuity theorem
- Shrinkage estimator
- Pesin theory
- Empirical process
- Binomial proportion confidence interval
- Lévy's upward theorem
- False discovery rate and the Benjamini–Hochberg procedure
- Particle filter
- Neyman construction
- Wilks' theorem
- Differentiable curve
- Skorokhod's embedding theorem
- Blaschke–Lebesgue theorem
- Permutation test
- Fisher's exact test
- Bonferroni correction
- Doob decomposition theorem
- Local asymptotic normality
- Frequentist inference
- Likelihood principle
- Chebyshev nodes
- Fisher–Neyman factorization theorem
- Girsanov theorem
- Quadratic variation
- Observed information
- Feller process
- Point estimation
- Local martingale
Further reading
- Web https://en.wikipedia.org/wiki/Construction_of_the_real_numbers, Construction from Cauchy sequences
About this page
| Tag | 0337CYB0VD |
|---|---|
| URI | m2://0337CYB0VD |
| Kind | definition |
| Writing | W0 stub |
| MSC | 26A03 |
| Defines | Order on the reals |
| Uses | Construction of the reals from Cauchy sequences, The rationals form an ordered field |
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