- Nominal.
- Ordinal.
- Interval.
- Ratio.
No category found.
- Independent samples t-test.
- Paired t-test.
- One-sample t-test.
- Two-sample z-test.
- Statistics.
- Mathematics.
- Biostatistics.
- Epidemiology.
- To immediately declare the drug unsafe.
- To rapidly analyze the data for patterns and statistical significance, to inform immediate public health action.
- To wait for more data to accumulate.
- To disregard the reports as anecdotal.
- Linear regression.
- Logistic regression.
- Poisson regression.
- Survival regression.
- Independent samples t-test.
- Paired t-test.
- Chi-square test of independence.
- One-way ANOVA.
- P-value.
- Correlation coefficient.
- T-statistic.
- Chi-square statistic.
- Mean.
- Median.
- Mode.
- Standard deviation.
- The drug is highly effective.
- The finding is statistically significant, but the effect estimate is imprecise and less reliable, warranting caution.
- The study had high precision.
- The study is invalid.
- Independent samples t-test.
- Paired t-test.
- Chi-square test.
- One-way ANOVA.
- Standard deviation.
- Variance.
- Range.
- Interquartile range.
- Logistic regression.
- Linear regression.
- Poisson regression.
- Survival regression.
- Odds.
- Relative risk.
- Incidence.
- Prevalence.
- z=(180?170)/5=2.0.
- z=180?170=10.
- z=5/(180?170)=0.5.
- z=170/5=34.
- To immediately recommend approval.
- To caution that a non-significant result might be due to low power (Type II error) rather than true ineffectiveness, necessitating further investigation.
- To ignore the power and focus on the p-value.
- To recommend disapproval regardless of findings.
- Type I error.
- Alpha error.
- Type II error.
- Sampling error.
- Logistic regression.
- Simple linear regression.
- Poisson regression.
- Multiple linear regression.
