Templat:Statistika

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| name = Statistika
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| title = Statistika
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| selected = 

| above =

• Outline
• Index

| abbr1 = descriptive
| section1 = Statistika Deskriptif
| list1 =
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   | group1 = Continuous data
   | list1 =
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      | groupstyle = font-weight:normal;
      | group1 = Pusat
      | list1 =

• Mean
  • aritmatik
  • geometrik
  • harmonik
• Median
• Modus

      | group2 = Sebaran
      | list2 =

• Varian
• Standar deviasi
• [[Koefisien variasi]
• Persentil
• Jangkauan
• Jangkauan Interkuartil

      | group3 = Shape
      | list3 =

• Teorema Limit Pusat
• Momen
  • Skewness
  • Kurtosis
  • L-moments

     }}

   | group2 = Count data
   | list2 =

• Index of dispersion

   | group3 = Summary tables
   | list3 =

• Grouped data
• Frequency distribution
• Contingency table

   | group4 = Dependence
   | list4 =

• Pearson product-moment correlation
• Rank correlation
  • Spearman's rho
  • Kendall's tau
• Partial correlation
• Scatter plot

   | group5 = Graphics
   | list5 =

• 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

  }}

| abbr2 = collection
| group2 = Pengumpulan Data
| list2 =

Study design	Population Statistic Effect size Statistical power Sample size determination Missing data
Survey methodology	Sampling stratified cluster Standard error Opinion poll Questionnaire
Controlled experiments	Design control optimal Controlled trial Randomized Random assignment Replication Blocking Interaction Factorial experiment
Uncontrolled studies	Observational study Natural experiment Quasi-experiment

| abbr3 = inference
| section3 = Statistika inferensia
| list3 =

Statistical theory	Population Statistic Probability distribution Sampling distribution Order statistic Empirical distribution Density estimation Statistical model Lp space Parameter location scale shape Parametric family Likelihood (monotone) Location–scale family Exponential family Completeness Sufficiency Statistical functional Bootstrap U V Optimal decision loss function Efficiency Statistical distance divergence Asymptotics Robustness
Frequentist inference	Point estimation Estimating equations Maximum likelihood Method of moments M-estimator Minimum distance Unbiased estimators Mean-unbiased minimum-variance Rao–Blackwellization Lehmann–Scheffé theorem Median unbiased Plug-in Interval estimation Confidence interval Pivot Likelihood interval Prediction interval Tolerance interval Resampling Bootstrap Jackknife Testing hypotheses 1- & 2-tails Power Uniformly most powerful test Permutation test Randomization test Multiple comparisons Parametric tests Likelihood-ratio Wald Score
Specific tests	Z-test (normal) Student's t-test F-test Goodness of fit Chi-squared G-test Kolmogorov–Smirnov Anderson–Darling Lilliefors Jarque–Bera Normality (Shapiro–Wilk) Likelihood-ratio test Model selection Cross validation AIC BIC Rank statistics Sign Sample median Signed rank (Wilcoxon) Hodges–Lehmann estimator Rank sum (Mann–Whitney) Nonparametric anova 1-way (Kruskal–Wallis) 2-way (Friedman) Ordered alternative (Jonckheere–Terpstra)
Bayesian inference	Bayesian probability prior posterior Credible interval Bayes factor Bayesian estimator Maximum posterior estimator

| abbr4 = correlation

| section4 =

• Correlation
• Regression analysis

| list4 =

Correlation	Pearson product-moment Partial correlation Confounding variable Coefficient of determination
Regression analysis	Errors and residuals Regression model validation Mixed effects models Simultaneous equations models Multivariate adaptive regression splines (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 regressions
Partition of variance	Analysis of variance (ANOVA, anova) Analysis of covariance Multivariate ANOVA Degrees of freedom

| abbr5 = analysis
| section5 = Categorical / Multivariate / Time-series / Survival analysis
| list5 =

Categorical	Cohen's kappa Contingency table Graphical model Log-linear model McNemar's test
Multivariate	Regression Manova Principal components Canonical correlation Discriminant analysis Cluster analysis Classification Structural equation model Factor analysis Multivariate distributions Elliptical distributions Normal
Time-series	General Decomposition Trend Stationarity Seasonal adjustment Exponential smoothing Cointegration Structural break Granger causality Specific tests Dickey–Fuller Johansen Q-statistic (Ljung–Box) Durbin–Watson Breusch–Godfrey Time domain Autocorrelation (ACF) partial (PACF) Cross-correlation (XCF) ARMA model ARIMA model (Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) Frequency domain Spectral density estimation Fourier analysis Wavelet Whittle likelihood
Survival	Survival function Kaplan–Meier estimator (product limit) Proportional hazards models Accelerated failure time (AFT) model First hitting time Hazard function Nelson–Aalen estimator Test Log-rank test

| abbr6 = applications
| section6 = Applications
| list6 =

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 statistics Psychometrics
Spatial statistics	Cartography Environmental statistics Geographic information system Geostatistics Kriging

| below =

• Category
• Portal
• Commons
• WikiProject

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