Medical Statistics is a discipline based on the basic principles of probability theory and mathematical statistics, and studies data collection, management and analysis in the field of medicine. Medical Statistics has been taught at Sun Yat-sen University for 44 years. It is a required course for all medical students of all levels.
Medical Statistics at Sun Yat-sen University was awarded as the National Excellent Course in 2008, the National Bilingual Model Course in 2010, the Provincial Online Excellent Course in 2011, the Distinguished English-based Course for International Students in China in 2013, and the Selected Online Public Course at Sun Yat-sen University in 2013. It was the first National MOOC course on Medical Statistics in 2014, and evaluated as the National Excellent Online Public Course in 2017. In addition, our teaching team has published many books of Medical Statistics in both Chinese and English, which have been reprinted several times.
In the context of the internationalization of education, our teaching team is committed to the development of English teaching and teaching materials. Since 1996, we have been teaching English course to eight-year medical students, graduate students, and international students. Our experience has been widely shared with our colleagues across the country.
The purpose of this course is to develop students' statistical thinking and application skills through study, and to provide them with a broad yet strong foundation of statistical methodologies, which is critical for the study of other courses, reading professional books or journals, engaging in medical practices, and conducting scientific research. The course is taught by the faculty members of the Department of Medical Statistics, School of Public Health, Sun Yat-sen University.
The main topics of this course include: Introduction and Basic Concepts of medical statistics, Descriptive Statistics, Probability and Distributions, Sampling Error and Confidence Interval, Hypothesis Testing for Continuous Variable, Analysis of Variance, Nonparametric Test Based on Ranks, Chi-square Test for Categorical Variable, Simple Correlation analysis, Simple Linear Regression, Statistical Principles of Experimental Design, and Statistical Table and Charts.
1.1 Marriage between Statistics & Medicine ---- Evolution within 200 years
1.2 Statistics ---- The natural affine of Public Health
1.3 Medical Statistics ---- Primary course for Health Professionals
1.4 Basic Concepts
Descriptive Statistics
2.1 Frequency Table and Histogram
2.2 Measurement for Average Level of a Sample
2.3 Measurement for Variation of a Sample
2.4 Relative Measures and Standardization Approaches
Probability and Distribution
3.1 Normal Distribution
3.2 Binomial Distribution
3.3 Poisson Distribution
3.4 Reference Range
Sampling Error and Confidence Interval
4.1 Distribution of Sample Means
4.2 t Distribution
4.3 Confidence Interval for Population Mean
4.4 Confidence Interval for Probability
Hypothesis Testing for Continuous Variables
5.1 Specific Logics of Hypothesis Testing
5.2 One sample t test and paired sample t test
5.3 Two independent samples t test
Analysis of Variance
6.1 Preparations for ANOVA
6.2 Completely Randomized Design and One-way ANOVA
6.3 Randomized Block Design and Two-way ANOVA
6.4 Multiple Comparisons and Preconditions of ANOVA
Nonparametric Test Based on Ranks
7.1.Basic logics of Nonparametric Tests based on ranks
7.2.Wilcoxon's signed rank sum test (matched pairs)
7.3.Wilcoxon's rank sum test (two samples)
7.4. Kruskal-Wallis' H test (k independent samples)
7.5.Friedman test (k groups of randomized block design)
Chi-square Test for Categorical Variable
8.1 Chi-square Test for Comparison between Two Independent Sample Proportions
8.2 Chi-square Tests for Binary Variables in a Paired Design
8.3 Chi-square Test for R×C Contingency Table
8.4 Chi-square Test for Goodness of Fit of a distribution
Simple Linear Correlation
9.1 Statistical description of linear correlation-Scatter plot
9.2 Statistical description of linear correlation-Pearson's correlation coefficient
9.3 Hypothesis testing for linear correlation
9.4 Preconditions and applications of linear correlation
9.5 Spearman's rank correlation
9.6 Association between Categorical Variables
Simple Linear Regression
10.1 Statistical description of linear regression
10.2 Hypothesis testing for linear regression
10.3 Preconditions and applications of linear regression
Statistical Principles of Experimental Design
11.1 Observational study vs Experimental study
11.2 Principles of Experimental Study and Error
11.3 Three elements of Experimental Study
11.4 Randomization controlled Trial
11.5 Randomization controlled Trial Study Case
Statistical Tables and Charts
12.1 Statistical Tables and Charts
