MODULE HANDBOOK
Module name Exploratory Data Analysis Module level, if applicable Bachelor
Code, if applicable SST-206 Subtitle, if applicable -
Courses, if applicable Exploratory Data Analysis Semester(s) in which the
module is taught 2th (second) Person responsible for the
module Chair of lab. Statistics Business, Social, and Industry
Lecturer
Dr. Jaka Nugraha, M.Si.
Mujiati Dwi Kartikasari, S.Si., M.Sc.
Ayundyah Kesumawati, S.Si., M.Si.
Language Bahasa Indonesia
Relation to curriculum Compulsory course in the first year (2th semester) Bachelor Degree Type of teaching, contact
hours 100 minutes lectures and 120 minutes structured activities per week.
Workload
Total workload is 90.67 hours per semester, which consists of 100 minutes lectures per week for 14 weeks, 120 minutes structured activities per week, 120 minutes individual study per week, in total is 16 weeks per semester, including mid exam and final exam.
Credit points 2
Requirements according to the examination regulations
Students have taken Exploratory Data Analysis course (SST-206) and have an examination card where the course is stated on.
Recommended prerequisites -
Module objectives/intended learning outcomes
After completing this course, the students have ability to:
CO 1. identify and explain research objects, variables, and types of data
CO 2. solve data pre-processing problems with data cleaning and data transformation
CO 3. make summaries of numerical data and categorical data CO 4. identify and explain data distribution
CO 5. master basic strategies for performing confirmatory statistical analysis
Content
Types of data (discrete and continuous) Data visualization (using R and Tableau) Summary of data
Data cleaning (standardization, transformation) Distribution of data (normal, t, and F distribution) Confirmatory statistical analysis
Study and examination requirements and forms of examination
The final mark will be weighted as follows:
No Assessment components
Assessment types
Weight (percentage)
1 CO 1 Quiz 20%
2 CO 2 Assignment 20%
3 CO 3 Assignment 20%
4 CO 4 Mid-term 20%
5 CO 5 Final exam 20%
Media employed White-board, Laptop, LCD Projector
Reading list
1. Wickham, Hadley. 2009. Elegant Graphics for Data Analysis.
Springer. New York.
2. Myatt, Glen J. 2007. Making Sense of Data. John Wiley & Sons.
Canada.
3. Peng, Roger D. 2015. Exploratory Data Analysis with R. Lean Publishing.
Mapping CO, PLO, and ASIIN’s SSC
ASIIN PLO
E N T H U S I A S T I C
Knowledge a b
c CO1
CO4 d
Ability e CO2
CO3 f
Competency g
h CO5
i j k l
