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Advanced Biostatistics

Course Description: The course is designed to highlight the importance of fundamental biostatistics concepts for oral epidemiology and dental research. The course will make students realize the significance of the role of biostatistics in monitoring global and regional trends in the distribution of oral disorders and in planning oral health care services. The course will facilitate students in acquiring the skills to infer conclusions from empirical data and to evaluate the statistics presented in scientific research.
Credit hours: 3
Objectives of the course :

Upon successful completion of this course, students will be able to:
1. Explanation of biostatistics and descriptive statistics highlighting their importance in oral healthcare.
Summarize data into tables and graphs.
3. Discussion of the concepts and practical application of probability and the normal distribution.
4. Calculate test statistics and confidence intervals for different types of data using statistical software.
5. Calculation of Kappa statistic for diagnostic consistency and inter-rater reliability using SPSS software.
6. Calculating summary statistics for a given dataset.
7. Interpretation of test statistics and confidence intervals for different data types using statistical software.
8. Interpretation of Kappa statistics for assessing diagnostic consistency and inter-rater reliability.

Course outputs :

1.0 Knowledge and Understanding
1.1 Explanation of Biostatistics and Descriptive Statistics, highlighting their importance in oral health care.
1.2 Description of Probability Concepts, the Normal Distribution, and Their Practical Applications.
1.3 Identifying the indicators and assumptions of statistical significance tests.
2.0 Skills
2.1 Interpretation of test statistics, p-values, and confidence intervals for different data types using statistical software.
2.2 Interpretation of Kappa Statistic to Evaluate Diagnostic Accuracy.
2.3 Sensitivity, specificity, positive predictive value, negative predictive value, false positive rate, false negative rate, and diagnostic accuracy of the indicator test.
2.4 Calculation/Statistics Summary statistics for a given dataset.
2.5 Calculating various test significance statistics, p-values, and confidence intervals for different data types using statistical software.
3.0 Values, autonomy and responsibility
Not applicable

Additional information:
  • Last updated: 2026-04-09

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