Probability and statistics academic disciplines . Statistical analysis often uses probability distributions , and the two topics are often studied together. However, probability theory contains much that is mostly of mathematical interest and not directly relevant to statistics. Moreover, many topics in statistics are independent of probability theory.
See also [ ] List of probability topics List of statistical topics Notation in probability and statistics External links [ ]
Descriptive statistics
Continuous data
Location Dispersion Shape
Variance Skewness Kurtosis Moments L-moments
Count data
Index of dispersion Summary tables
Grouped data Frequency distribution Contingency table Dependence Statistical graphics
Bar chart Biplot Box plot Control chart Correlogram Fan chart Forest plot Histogram Pie chart Q–Q plot Run chart Scatter plot Stemplot Radar chart
Data collection
Designing studies
Effect size Standard error Statistical power Sample size determination Survey methodology
Sampling Stratified sampling Cluster sampling Opinion poll Questionnaire Controlled experiment
Design of experiments Randomized experiment Random assignment Replication Blocking Factorial experiment Optimal design Uncontrolled studies
Natural experiment Quasi-experiment Observational study
Statistical inference
Statistical theory
Sampling distribution Order statistic Scan statistic Record value Sufficiency Completeness Exponential family Permutation test (Randomization test )Empirical distribution Bootstrap U statistic Efficiency Asymptotics Robustness Frequentist inference
Unbiased estimator (Mean unbiased minimum variance , Median unbiased )Biased estimators (Maximum likelihood , Method of moments , Minimum distance , Density estimation )
Confidence interval Testing hypotheses Power Parametric tests (Likelihood-ratio , Wald , Score ) Specific tests
Z (normal)Student's t -test F Goodness of fit (Chi-squared , G Sample source , sample normality , Skewness & kurtosis Normality , Model comparison , Model quality )Signed-rank (1-sample , 2-sample , 1-way anova )Shapiro–Wilk Kolmogorov–Smirnov Bayesian inference
Bayesian probability Prior Posterior Credible interval Bayes factor Bayesian estimator Maximum posterior estimator
Correlation and regression analysis
Correlation Regression analysis
Errors and residuals Regression model validation Mixed effects models Simultaneous equations models MARS Linear regression
Simple linear regression Ordinary least squares General linear model Bayesian regression Non-standard predictors
Nonlinear regression Nonparametric Semiparametric Isotonic Robust Heteroscedasticity Homoscedasticity Generalized linear model
Exponential families Logistic (Bernoulli) Binomial Poisson Partition of variance
Analysis of variance (ANOVA) Analysis of covariance Multivariate ANOVA Degrees of freedom
Categorical , multivariate , time-series , or survival analysis
Categorical data
Cohen's kappa Contingency table Graphical model Log-linear model McNemar's test Multivariate statistics
Multivariate regression Principal components Factor analysis Cluster analysis Classification Copulas Time series analysis
General
Decomposition Trend Stationarity Seasonal adjustment Exponential smoothing Cointegration Specific tests
Granger causality Q-Statistic Durbin–Watson Time domain
ACF PACF XCF ARMA model ARIMA model ARCH Vector autoregression Frequency domain
Spectral density estimation Fourier analysis Wavelet
Survival analysis
Survival function Kaplan–Meier Logrank test Failure rate Proportional hazards models Accelerated failure time model
Applications
Biostatistics
Bioinformatics Clinical trials & studies Epidemiology Medical statistics Engineering statistics
Chemometrics Methods engineering Probabilistic design Process & Quality control Reliability System identification Social statistics
Actuarial science Census Crime statistics Demography Econometrics National accounts Official statistics Population Psychometrics Spatial statistics
Cartography Environmental statistics Geographic information system Geostatistics Kriging
