- Reject the null hypothesis.
- Fail to reject the null hypothesis.
- Accept the alternative hypothesis.
- The result is statistically significant.
Category: Introduction To Biostatistics
- Range.
- Interquartile range.
- Standard deviation.
- Median.
- Continuous.
- Discrete.
- Nominal.
- Ordinal.
- Linear regression.
- Logistic regression.
- Survival analysis.
- ANOVA.
- Independent samples t-test.
- Paired t-test.
- Chi-square test of independence.
- One-way ANOVA.
- The probability of making a Type II error.
- The probability of correctly rejecting the null hypothesis.
- The maximum acceptable probability of making a Type I error (false positive).
- The power of the test.
- To immediately accept the findings.
- To critically evaluate the potential for selection bias and its impact on the validity of the results.
- To ignore the methods and focus only on the p-value.
- To ask the researchers to collect more data.
- T-test.
- Chi-square test.
- Linear regression.
- Survival analysis (e.g., Kaplan-Meier or Cox regression).
- Correlation implies causation.
- The correlation is likely due to chance.
- Correlation does not imply causation; confounding or other factors may be at play.
- The study was poorly designed.
- Independent samples t-test.
- Paired t-test.
- Chi-square test.
- One-way ANOVA.
- 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.
- Bar chart.
- Pie chart.
- Histogram.
- Line graph.
- Mean.
- Standard deviation.
- Correlation coefficient.
- P-value.
