Course Name Code Semester T+U Hours Credit ECTS
Statistical Applications With Python YBS 368 6 2 + 0 2 5
Precondition Courses <p>Data structures and Statistics</p>
Recommended Optional Courses
Course Language Turkish
Course Level Bachelor's Degree
Course Type Optional
Course Coordinator Doç.Dr. NİHAL SÜTÜTEMİZ
Course Lecturers
Course Assistants

Res.Assist. Bahadır AKTAŞ

Course Category Field Proper Education
Course Objective

Current applications of the theory by performing a statistical software with Python, students gain the ability to analyze data with appropriate methods.

Course Content
# Course Learning Outcomes Teaching Methods Assessment Methods
1 Lecture, Testing,
2 Lecture, Testing,
3 Lecture, Testing,
4 Lecture, Question-Answer, Testing,
5 Lecture, Question-Answer, Drilland Practice, Testing,
6 Lecture, Question-Answer, Drilland Practice, Testing, Homework,
7 Lecture, Question-Answer, Drilland Practice, Testing, Homework,
8 Lecture, Question-Answer, Drilland Practice, Testing, Homework,
9
10 Lecture, Question-Answer, Drilland Practice, Testing, Homework,
11 Lecture, Question-Answer, Drilland Practice, Testing, Homework,
12 Lecture, Question-Answer, Drilland Practice, Testing, Homework,
13 Lecture, Question-Answer, Drilland Practice, Testing, Homework,
14 Lecture, Question-Answer, Drilland Practice, Testing, Homework,
Week Course Topics Preliminary Preparation
1 Data Structures and Variables
2 Data Loading, Editing and Function Defining
3 Loops
4 Ecosystem of Python Data Science and Basic Concepts of Statistics
5 Data Visualization
6 Descriptive Statistics in Python
7 Probability Distributions
8 Probability Distributions
9 Midterm exam
10 Parametric Comparison Tests For Two Population
11 Parametric Variance Analysis
12 Non-Parametric Comparison Tests For Two Population
13 Nonparametric Analysis of Variance
14 Correlation and Regression Analysis
Resources
Course Notes
Course Resources

McKinney,W., (2013), Python For Data Analysis, O’Reilly, USA.

Başer, M. (2017), Python, Dikeyeksen, İstanbul.

Order Program Outcomes Level of Contribution
1 2 3 4 5
1 Can follow new and current technologies and evaluate them
2 Can understand the operation of Corporate Information Systems and use these systems at a basic level X
3 Constructs numerical models of basic business problems. X
4 Solves modeled business problems with the help of information technologies and interprets the solutions X
5 Contributes to informatics oriented projects as a member of the team X
6 Effectively uses information technology tools that support teamwork in project management. X
7 Master basic business functions and information technologies and establishes the link between them X
8 Contributes to the design, development and implementation processes of corporate information systems. X
9 Can produce and present quality documentation for all kinds of projects, including entrepreneurship projects.
10 Prepares informative, effective and interesting presentations and presents these presentations. X
Evaluation System
Semester Studies Contribution Rate
1. Ara Sınav 50
1. Ödev 30
1. Kısa Sınav 10
2. Kısa Sınav 10
Total 100
1. Yıl İçinin Başarıya 50
1. Final 50
Total 100
ECTS - Workload Activity Quantity Time (Hours) Total Workload (Hours)
Course Duration (Including the exam week: 16x Total course hours) 16 2 32
Mid-terms 1 20 20
Quiz 2 15 30
Assignment 1 30 30
Final examination 1 20 20
Total Workload 132
Total Workload / 25 (Hours) 5.28
dersAKTSKredisi 5