In the comparison of statistical procedures, efficiency is a measure of an estimator's quality. This would be about the estimator of an experimental design, or of a hypothesis testing procedure.[2] Basically, a more efficient estimator, experiment, or test needs fewer observations than a less efficient one to get a given performance.
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Continuous data | |
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Count data | |
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Summary tables | |
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Dependence | |
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Graphics |
- Bar chart
- Biplot
- Box plot
- Control chart
- Correlogram
- Fan chart
- Forest plot
- Histogram
- Pie chart
- Q–Q plot
- Run chart
- Scatter plot
- Stem-and-leaf display
- Radar chart
- Violin plot
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Study design |
- Population
- Statistic
- Effect size
- Statistical power
- Optimal design
- Sample size determination
- Replication
- Missing data
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Survey methodology | |
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Controlled experiments | |
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Adaptive Designs |
- Adaptive clinical trial
- Up-and-Down Designs
- Stochastic approximation
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Observational Studies |
- Cross-sectional study
- Cohort study
- Natural experiment
- Quasi-experiment
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Statistical theory | |
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Frequentist inference | Point estimation |
- Estimating equations
- Unbiased estimators
- Mean-unbiased minimum-variance
- Rao–Blackwellization
- Lehmann–Scheffé theorem
- Median unbiased
- Plug-in
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Interval estimation | |
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Testing hypotheses |
- 1- & 2-tails
- Power
- Uniformly most powerful test
- Permutation test
- Multiple comparisons
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Parametric tests |
- Likelihood-ratio
- Score/Lagrange multiplier
- Wald
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Specific tests | | Goodness of fit | |
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Rank statistics |
- Sign
- Signed rank (Wilcoxon)
- Rank sum (Mann–Whitney)
- Nonparametric anova
- 1-way (Kruskal–Wallis)
- 2-way (Friedman)
- Ordered alternative (Jonckheere–Terpstra)
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Bayesian inference | |
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Correlation | |
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Regression analysis |
- Errors and residuals
- Regression validation
- Mixed effects models
- Simultaneous equations models
- Multivariate adaptive regression splines (MARS)
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Linear regression | |
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Non-standard predictors |
- Nonlinear regression
- Nonparametric
- Semiparametric
- Isotonic
- Robust
- Heteroscedasticity
- Homoscedasticity
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Generalized linear model | |
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Partition of variance |
- Analysis of variance (ANOVA, anova)
- Analysis of covariance
- Multivariate ANOVA
- Degrees of freedom
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Categorical / Multivariate / Time-series / Survival analysis |
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Categorical |
- Cohen's kappa
- Contingency table
- Graphical model
- Log-linear model
- McNemar's test
- Cochran-Mantel-Haenszel statistics
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Multivariate |
- Regression
- Manova
- Principal components
- Canonical correlation
- Discriminant analysis
- Cluster analysis
- Classification
- Structural equation model
- Multivariate distributions
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Time-series | General |
- Decomposition
- Trend
- Stationarity
- Seasonal adjustment
- Exponential smoothing
- Cointegration
- Structural break
- Granger causality
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Specific tests |
- Dickey–Fuller
- Johansen
- Q-statistic (Ljung–Box)
- Durbin–Watson
- Breusch–Godfrey
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Time domain |
- Autocorrelation (ACF)
- Cross-correlation (XCF)
- ARMA model
- ARIMA model (Box–Jenkins)
- Autoregressive conditional heteroskedasticity (ARCH)
- Vector autoregression (VAR)
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Frequency domain | |
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Survival | Survival function |
- Kaplan–Meier estimator (product limit)
- Proportional hazards models
- Accelerated failure time (AFT) model
- First hitting time
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Hazard function | |
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Test | |
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Applications |
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Biostatistics | |
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Engineering statistics |
- Chemometrics
- Methods engineering
- Probabilistic design
- Process / quality control
- Reliability
- System identification
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Social statistics | |
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Spatial statistics |
- Cartography
- Environmental statistics
- Geographic information system
- Geostatistics
- Kriging
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