From Simple English Wikipedia, the free encyclopedia
Statistical surveys are collections of information about items in a population.
Surveys can be grouped into numerical and categorical types. A numerical survey is to get numbers as replies. For example:
How many minutes, on average, do you spend eating breakfast?
This survey question is used to generate numbers in minutes. An example of a categorical question is:
What is your favorite color?
The categories for this would be yellow, green, purple, etc... which are not numbers.
Surveys of human populations and institutions are common in political polling and government, health, social science and marketing research. A survey may concentrate on opinions or factual information depending on its purpose.
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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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