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Explore the main themes, entities and connections around Statistical hypothesis test. Start with the topic map, then use the sections below for research and deeper semantic analysis.
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History
Definition of terms
Modern origins and early controversy
Alternatives
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Topics to explore
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Overview
- Test statistic
- Critical value Critical value (statistics)
- Probability value P-value
- One-tailed One- and two-tailed tests
- Region of rejection Statistical hypothesis testing
- Unbiased test
- Lady tasting tea
Definition of terms
- Statistical population
- Sample data Sampling (statistics)
- Random variable
- Literature review
- Conditional probability
- Significance level
- Type I and type II errors
- Power Power (statistics)
- Size Size (statistics)
- False positive
- Biostatistics
- Sensitivity and specificity
- Statistically significant Statistical significance
- Exact test
- Statistical inference
- Uniformly most powerful test
History
- John Arbuthnot
- Pierre-Simon Laplace
- Human sex ratio
- § Human sex ratio Statistical hypothesis test
- Pierre Laplace
- Karl Pearson
- Chi squared test
- Weldon dice throw data Walter Frank Raphael Weldon
- Contingency Contingency table
- Independent Statistical independence
- Principle of indifference
- Ronald Fisher's Ronald Fisher
- Jerzy Neyman
- Egon Pearson
- Neyman–Pearson lemma
Modern origins and early controversy
- Pearson's chi-squared test
- William Sealy Gosset
- Student's t-distribution
- Null hypothesis
- Analysis of variance
- Gaussian distributions Gaussian distribution
- Type II error
- Faith Fiducial inference
- Inductive inference
- The Design of Experiments
- University of California, Berkeley
- Raymond S. Nickerson
- Signal detection Detection theory
Technical description of the null hypothesis
Philosophy
Education
Principle
- Sample Sample (statistics)
- Controlled experiment
Goals of null hypothesis tests
- Homogeneity Homogeneity (statistics)
- Mutually illuminating Confidence interval
Choice of the null hypothesis
- David Cox David Cox (statistician)
- Testing hypotheses suggested by the data
- Circular reasoning
- Randomized Randomized controlled trial
- Placebo-controlled Placebo-controlled study
- Double-blind Blinded experiment
- One-tailed test
Performing a frequentist hypothesis test in practice
Nonparametric bootstrap hypothesis testing
- Resampling Resampling (statistics)
Examples
- Sign test
- Non-parametric test
- Muriel Bristol
- Clairvoyance
- Suits Suit (cards)
- False negative
- Presumed Presumption
- Type I error
- Results actually observed Realization (probability)
Variations and sub-classes
- Frequentist inference
- Bayesian inference
- Decision theory
- Bayesian Bayesian statistics
- Posterior probability
- Bayesian decision theory
- Optimal decisions Optimal decision
- Power Statistical power
- Sample size determination
Neyman–Pearson hypothesis testing
- Likelihood ratio Likelihood-ratio test
- Proving a negative Philosophic burden of proof
- Falsifiable Falsifiability
- Tukey John Tukey
- Statistical process control
- Game theory
Criticism
Alternatives
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Map overview Semantic statistics
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.Statistical hypothesis test
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Statistical hypothesis test
Top relations
Important terminology Word statistics
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Important terminology
hypothesis null test testing statistical significance probability neyman data pearson fisher alternative tests hypotheses statistics example sample one-tailed true effect
Entity relationships Subject–Predicate–Object triples
Extracted RDF-like relationships with confidence and source. The table includes structured facts and lower-confidence contextual relations.| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Statistical hypothesis test | is a | method of statistical inference used to decide whether the data provide sufficient evidence to reject a particular hypothesis | 0.90 | text |
| the normal distribution or t-distribution to determine the probability of obtaining test results at least as extreme as the results actually observed | instance of | the test statistic variables are assumed to follow a certain probability distribution | 0.80 | text |
| under the assumption that the null hypothesis is correct | instance of | the test statistic variables are assumed to follow a certain probability distribution | 0.80 | text |
| which is defined as the p-value | instance of | the test statistic variables are assumed to follow a certain probability distribution | 0.80 | text |
| Statistical hypothesis test | related to Criticism | Much | 0.60 | section |
| Statistical hypothesis test | related to Criticism | The | 0.60 | section |
| Statistical hypothesis test | related to Criticism | Confusion | 0.60 | section |
| Statistical hypothesis test | related to Criticism | Fisher | 0.60 | section |
| Statistical hypothesis test | related to Criticism | Neyman | 0.60 | section |
| Statistical hypothesis test | related to Criticism | Pearson | 0.60 | section |
| Statistical hypothesis test | related to Criticism | Emphasis | 0.60 | section |
| Statistical hypothesis test | related to Criticism | Rigidly | 0.60 | section |
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