Nevşehir Hacı Bektaş Veli University Course Catalogue

Information Of Programmes

INSTITUTE OF SOCIAL SCIENCES / MUD-513 - ACCOUNTING AND AUDITING (MASTER'S DEGREE WITHOUT THESIS)

Code: MUD-513 Course Title: DATA ANALYSIS Theoretical+Practice: 3+0 ECTS: 6
Year/Semester of Study 1 / Fall Semester
Level of Course 2nd Cycle Degree Programme
Type of Course Optional
Department ACCOUNTING AND AUDITING (MASTER'S DEGREE WITHOUT THESIS)
Pre-requisities and Co-requisites None
Mode of Delivery Face to Face
Teaching Period 14 Weeks
Name of Lecturer SERKAN DERİCİ (serkanderici@nevsehir.edu.tr)
Name of Lecturer(s)
Language of Instruction Turkish
Work Placement(s) None
Objectives of the Course
In today's digital age, there are many data sources in daily and professional life. Everything from our smartphones to sensors, from computer programs to vehicles produces data at all times. In this respect, knowing the types of data and using them effectively by analyzing them is important for developing successful policies. In this context, the aim of this course is to provide individuals with the ability to professionally identify, securely store, classify and analyze and interpret data types.

Learning Outcomes PO MME
The students who succeeded in this course:
LO-1 Can use basic level analytical thinking skills when faced with problems. PO-1 Based on the 4-year undergraduate level qualifications in the field of business administration or if they have undergraduate education in another field, students who have taken the necessary courses and have reached this qualification can develop and deepen their knowledge in the field of accounting at the level of expertise.
Examination
LO-2 Can solve problems using classical decision-making techniques. PO-1 Based on the 4-year undergraduate level qualifications in the field of business administration or if they have undergraduate education in another field, students who have taken the necessary courses and have reached this qualification can develop and deepen their knowledge in the field of accounting at the level of expertise.
Examination
LO-3 Can exhibit a professional approach in decision-making processes regarding business processes. PO-1 Based on the 4-year undergraduate level qualifications in the field of business administration or if they have undergraduate education in another field, students who have taken the necessary courses and have reached this qualification can develop and deepen their knowledge in the field of accounting at the level of expertise.
Examination
PO: Programme Outcomes
MME:Method of measurement & Evaluation

Course Contents
Starting from the concept of data, this course covers the learning of data types, digital and traditional storage possibilities, classification, analysis and reporting.
Weekly Course Content
Week Subject Learning Activities and Teaching Methods
1 Introduction to Data Science and Its Importance Today Lecture, Question and Answer, Problem Solving
2 Historical Development of Data Science and Types of Data Lecture, Question and Answer, Problem Solving
3 Data Collection and Sampling Methods Lecture, Question and Answer, Problem Solving
4 Descriptive Statistics: Frequency Distribution, Central Tendency and Variability Measures Lecture, Question and Answer, Problem Solving
5 Statistical Estimation and Hypothesis Testing Lecture, Question and Answer, Problem Solving
6 Simple and Partial Correlation, Parametric Hypothesis Tests: T-Test and Z-Test Lecture, Question and Answer, Problem Solving
7 Nonparametric Hypothesis Tests: Chi-Square, Mann Whitney U Lecture, Question and Answer, Problem Solving
8 mid-term exam
9 SPPS and Python Applications Lecture, Question and Answer, Problem Solving
10 Analysis of Variance (ANOVA) and Kruskal-Wallis Tests Lecture, Question and Answer, Problem Solving
11 Simple/Multiple Linear Regression and Correlation Analysis Lecture, Question and Answer, Problem Solving
12 Factor and Cluster Analysis Lecture, Question and Answer, Problem Solving
13 Introduction to Machine Learning: MATLAB and Python Application Lecture, Question and Answer, Problem Solving
14 Introduction to Machine Learning: MATLAB and Python Application Lecture, Question and Answer, Problem Solving
15 Data Visualization Lecture, Question and Answer, Problem Solving
16 final exam
Recommend Course Book / Supplementary Book/Reading
1 Büyüköztürk, Ş. (2018). Veri Analizi El Kitabı, Pegem Akademi, 24. Baskı, Ankara.
2 Kalaycı, E. (2010). SPSS Uygulamalı Çok Değişkenli İstatistik Teknikleri, Asil Yayın D., 5. Baskı, Ankara.
Required Course instruments and materials
Textbooks, Notebook, Blackboard

Assessment Methods
Type of Assessment Week Hours Weight(%)
mid-term exam 8 1 40
Other assessment methods
1.Oral Examination
2.Quiz
3.Laboratory exam
4.Presentation
5.Report
6.Workshop
7.Performance Project
8.Term Paper
9.Project
final exam 16 1 60

Student Work Load
Type of Work Weekly Hours Number of Weeks Work Load
Weekly Course Hours (Theoretical+Practice) 3 14 42
Outside Class
       a) Reading 3 14 42
       b) Search in internet/Library 3 14 42
       c) Performance Project 0
       d) Prepare a workshop/Presentation/Report 0
       e) Term paper/Project 0
Oral Examination 0
Quiz 0
Laboratory exam 0
Own study for mid-term exam 3 7 21
mid-term exam 2 1 2
Own study for final exam 4 7 28
final exam 3 1 3
0
0
Total work load; 180