Types I and II errors in significance tests
December 28, 2017
Training and consultancy for testing laboratories.
Tag Cloud
- ANOVA
- Design of Experiments
- Linear regression
- Significance testing
- Randomization
- Probability
- Sampling statistics
- outliers
- Normal distribution
- Sampling
- Probability distribution
- Sampling uncertainty
- GUM
- Median
- uncertainty
- Microbiology
- Student's t-distribution
- F-test
- Degrees of freedom
- Control chart
- Decision rules
- Measurement error
- Confidence interval
- propagation of uncertainty
- Monte Carlo
- Anderson-Darling
- Variance
- Type I and II errors
- hypothesis testing
- Risk
- Conformity testing
- t-test
- p-Value
- ISO 17025
- Decision Rule
- profiency testing
- standard uncertainty
- measurement uncertainty
- Confidence limits
- Detection limit
- interlab comparison
- Central limit theorem
- IQR
- Law of Averages
- Coverage factor
- Precision
- Accuracy
- How to
- ISO FDIS 17025
- Bias
- Risk assessment
- Risk analysis
- Cross-checks
- Factorial design
- Chi-square
- quartile
- Divisor
- Aerobic plate count
- Compliance
- ISO 17025:2017
- Recovery
- Shewhart
- She
- Method validation
- Excel spreadsheet
- Trueness
- Mean value
- analytical uncertainty
- standard additions method
Comments on: "Types I and II errors in significance tests" (1)
[…] had discuss these two types of error in the short articles: https://consultglp.com/2017/12/28/type-i-and-type-ii-errors-in-significance-tests/ , and, […]