No

Module Name

Biostatistics

1

Code of Subjects

P10A02.0728

2

Study load

2(2-0) credits

Contact hour per semester: 27

Independent study hour per semester : 64

Total workload : 91

3

Semester

7

4

Precondition

There is no

5

Competence

After completing this topic, 

1. Students are able to understand the concepts and applications of biostatistics in research.
2. Students are able to understand research design and types of experimental and observational research.
3. Students are able to understand descriptive statistics, define and present data elements in research, and perform data visualization.
4. Students are able to understand the concept of frequency distribution including distribution, average, measurement of central tendency, standard deviation and standard error and are able to identify outliers and missing data.
5. Students are able to understand and explain the concept of probability and probability distribution.
6. Students are able to understand and perform minimal sample calculations in research and are able to perform sampling techniques.
7. Students are able to understand the concept of hypothesis, hypothesis testing, types of errors in biostatistics (type 1 and type 2 error), and understand the concept of p-value and confidence interval.
8. Students are able to understand, perform, and interpret parametric and non-parametric difference tests from 2 or more groups and analysis of variance using statistical software (e.g. SPPS).
9. Students are able to understand, perform, and interpret correlation tests and linear regression techniques as well as univariate and multivariate logistics using statistical software (e.g. SPPS).

6

Elements of Competency

MKK

7

Type Competency

Main competence

8

Syllabus

The Biostatistics course discusses the application and use of statistics in its design, analysis, and interpretation in medical and clinical research (experimental and observational). The focus of discussion in this course includes the concept of biostatistics in research, elements of research design, defining data, presenting data, hypothesis concepts, hypothesis testing, sampling techniques, sampling distribution concepts, parametric and non-parametric test concepts, analysis of variance, correlation, and regression techniques.

9

Attribute Soft Skill

Ethics, awareness, discipline

10

Learning methods

Presentation, lecturer, discussion, project

11

Learning Media

LCD Projector

12

Appraisal

Assignment : 10%

Quiz : 10% 

Mid-Exam : 40%

Final-Exam : 40%

13

Lecturer

Neily Zakiyah and Sofa Dewi Alfian

14

References

1. Statistics in Medicine, 4th edition. Riffenburgh, RH. Elsevier. 2012
   
2. Fundamental of Biostatistics, 8th edition. Rosner, B. Cengage Learning. 2015