Type I and type II errors in significance tests
Types I and II errors in significance tests
December 28, 2017
Training and consultancy for testing laboratories.
Tag Cloud
- ANOVA
- Design of Experiments
- Randomization
- Probability
- Linear regression
- Significance testing
- Sampling statistics
- Sampling
- outliers
- Probability distribution
- uncertainty
- Microbiology
- GUM
- Control chart
- Normal distribution
- Confidence interval
- Degrees of freedom
- Median
- Monte Carlo
- Anderson-Darling
- Risk
- Decision rules
- Conformity testing
- Sampling uncertainty
- Measurement error
- F-test
- t-test
- propagation of uncertainty
- p-Value
- ISO 17025
- Decision Rule
- Confidence limits
- Central limit theorem
- IQR
- Variance
- Law of Averages
- Coverage factor
- Type I and II errors
- How to
- ISO FDIS 17025
- Bias
- Cross-checks
- Detection limit
- Factorial design
- Chi-square
- interlab comparison
- quartile
- Divisor
- Precision
- Accuracy
- Aerobic plate count
- Compliance
- hypothesis testing
- ISO 17025:2017
- Recovery
- Shewhart
- She
- Student's t-distribution
- Method validation
Leave a Reply