A t-test is a statistical hypothesis test. People use it when they want to compare a mean (average) of a measurement from one group A to some theoretical, expected value. People also use it when they want to compare the mean (average) of a measurement of two groups A and B. They want to decide if the mean in group A is different to the theoretical value or to the mean in group B.
Example
For example, pretend there are two groups of people. One group exercises a lot and the other doesn't. Do the people who exercise tend to live longer than those who don't? Then the property of interest is the average life time. Is the average life time of people who exercise different to the average life time of people who don't? A t-test can help answer this question.
When this is used
The t-test is used when the property's variance in the groups is unknown. When people want to do the t-test they have to calculate the variance from the sample (the collection of data). This calculated variance is almost always different to the true variance in the group. The t-test was created to care about this difference.
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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
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- Classification
- Structural equation model
- Multivariate distributions
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| Time-series | | General |
- Decomposition
- Trend
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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
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- System identification
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| Social statistics | |
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| Spatial statistics |
- Cartography
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- Geographic information system
- Geostatistics
- Kriging
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