- Independent samples t-test.
- Paired t-test.
- Chi-square test.
- One-way ANOVA.
No category found.
- Binomial distribution.
- Poisson distribution.
- Normal distribution.
- Exponential distribution.
- Type I error.
- Type II error.
- Sampling error.
- Measurement error.
- To reduce the cost of the trial.
- To prevent bias in the assessment of outcomes due to participant or researcher expectations.
- To make data analysis easier.
- To ensure all participants receive the active drug.
- Mean.
- Standard deviation.
- Correlation coefficient.
- P-value.
- Paired t-test.
- Chi-square test.
- Independent samples t-test.
- ANOVA.
- P-value.
- Confidence interval.
- Statistical power and sample size calculation.
- Mean.
- Mean.
- Median.
- Mode.
- Standard deviation.
- There is a 0.1% chance that the drug is ineffective.
- The probability of observing results as extreme as, or more extreme than, those obtained, assuming the null hypothesis is true.
- The probability that the null hypothesis is true.
- The probability of making a Type I error.
- One-tailed (right-tailed) test.
- One-tailed (left-tailed) test.
- Two-tailed test.
- Directional test.
- Intercept.
- Residual.
- R-squared.
- Slope coefficient (?1?).
- Standard deviation.
- Variance.
- Standard error of the mean.
- Interquartile range.
- To attribute all changes to the new policy.
- To urgently highlight the potential for confounding and the need to consider and, if possible, adjust for other concurrent changes.
- To ignore other factors.
- To assume the policy is the only cause.
- The drug increases the hazard of the event.
- The drug decreases the hazard of the event, and the result is statistically significant as the interval does not include 1.0.
- The drug has no effect.
- The hazard ratio is too high.
- Independent samples t-test.
- Paired t-test.
- Chi-square test of independence.
- One-way ANOVA.
