Nevşehir Hacı Bektaş Veli University Course Catalogue

Information Of Programmes

TOURISM RESEARCH INSTITUTE / TUİ604 - TOURISM MANAGEMENT (DOCTORATE DEGREE)

Code: TUİ604 Course Title: MULTIVARIATE STATISTICAL METHODS Theoretical+Practice: 3+0 ECTS: 6
Year/Semester of Study 1 / Spring Semester
Level of Course 3rd Cycle Degree Programme
Type of Course Compulsory
Department TOURISM MANAGEMENT (DOCTORATE DEGREE)
Pre-requisities and Co-requisites None
Mode of Delivery Face to Face
Teaching Period 14 Weeks
Name of Lecturer DUYGU EREN (deren@nevsehir.edu.tr)
Name of Lecturer(s)
Language of Instruction Turkish
Work Placement(s) None
Objectives of the Course
To introduce the concepts and methods of multivariate analysis and to provide exercises in the application of multivariate data analysis to related problems..

Learning Outcomes PO MME
The students who succeeded in this course:
LO-1 Apply knowledge of Multivariate Statistics . PO-4 Plan, conduct, evaluate and report a study using scientific research methods.
PO-10 Analyze, critically interpret and evaluate the knowledge and skills they have gained.
Examination
Laboratory Exam
Presentation
LO-2 design and conduct experiments as well as to analyze and interpret data PO-4 Plan, conduct, evaluate and report a study using scientific research methods.
PO-10 Analyze, critically interpret and evaluate the knowledge and skills they have gained.
Examination
Laboratory Exam
Presentation
LO-3 identify, formulate and solve real life problems PO-4 Plan, conduct, evaluate and report a study using scientific research methods.
PO-10 Analyze, critically interpret and evaluate the knowledge and skills they have gained.
Examination
Laboratory Exam
Presentation
LO-4 understand local and global effects of Statistics and its applications PO-4 Plan, conduct, evaluate and report a study using scientific research methods.
PO-10 Analyze, critically interpret and evaluate the knowledge and skills they have gained.
Examination
Laboratory Exam
Presentation
LO-5 Usage of statistical package program and software knowledge to solve real life problems PO-4 Plan, conduct, evaluate and report a study using scientific research methods.
PO-10 Analyze, critically interpret and evaluate the knowledge and skills they have gained.
Examination
Laboratory Exam
Presentation
LO-6 Usage of statistical package program and software knowledge to solve real life problems PO-4 Plan, conduct, evaluate and report a study using scientific research methods.
PO-10 Analyze, critically interpret and evaluate the knowledge and skills they have gained.
Examination
Laboratory Exam
Presentation
PO: Programme Outcomes
MME:Method of measurement & Evaluation

Course Contents
Multivariate data analysis and its application areas, data matrices and measurement scales, the multivariate normal distribution (MND), inferences about a mean vector, comparisons of several multivariate means, cluster analysis, discriminant analysis, logistic regression analysis, Principal component and factor analysis, Canonical correlation, multidimensional scaling.
Weekly Course Content
Week Subject Learning Activities and Teaching Methods
1 Statistics and multivariate data analysis and its application areas Representing subjects. Question and answer. Solving problems technique.
2 Data preparation and descriptive statistics Representing subjects. Question and answer. Solving problems technique. Computer application.
3 Normal distribution Representing subjects. Question and answer. Solving problems technique. Computer application.
4 Parametric hypothesis testing Representing subjects. Question and answer. Solving problems technique. Computer application.
5 Nonparametric hypothesis testing Representing subjects. Question and answer. Solving problems technique. Computer application.
6 Correlation and regression analysis Representing subjects. Question and answer. Solving problems technique. Computer application.
7 Regression analysis Representing subjects. Question and answer. Solving problems technique. Computer application.
8 mid-term exam
9 Logistic regression analysis Representing subjects. Question and answer. Solving problems technique. Computer application.
10 Exploratory factor analysis Representing subjects. Question and answer. Solving problems technique. Computer application.
11 Cluster analysis Representing subjects. Question and answer. Solving problems technique. Computer application.
12 Discriminant analysis Representing subjects. Question and answer. Solving problems technique. Computer application.
13 Reliability and validity Question and answer. Computer application. Student presentation.
14 Confirmatory factor analysis Question and answer. Computer application. Student presentation.
15 Structural equation modeling Question and answer. Computer application. Student presentation.
16 final exam
Recommend Course Book / Supplementary Book/Reading
1 Hair, J. D., Anderson, R. E., Tatham, R. L. ve Black, W. C., (2010). Multivariate Data Analysis (7th Ed.). New Jersey: Pearson Education, Inc.
2 Kurtuluş, K. (2004). Pazarlama Araştırmaları (8. Bas.). İstanbul: Literatür Yayıncılık.
3 Altunışık, R., Coşkun, R., Bayraktaroğlu, S. ve Yıldırım, E. (2007). Sosyal Bilimlerde Araştırma Yöntemleri. Sakarya: Sakarya Yayıncılık.
4 Nakip, M. (2003). Pazarlama Araştırmaları: Teknikler ve SPSS Destekli Uygulamalar. İstanbul: Seçkin Yayıncılık.
5 Gürbüz, S., & Şahin, F. (2014). Sosyal bilimlerde araştırma yöntemleri. Ankara: Seçkin Yayıncılık.
6 Karagöz, Y. (2018). SPSS ve AMOS Uygulamalı Bilimsel Araştırma Yöntemleri ve Yayın Etiği, Ankara: Nobel Akademik Yayıncılık.
7 Karagöz, Y. (2016). SPSS - AMOS - META Uygulamalı İstatistiksel Analizler, Ankara: Nobel Akademik Yayıncılık.
8 Alpar, R. (2017). Uygulamalı Çok Değişkenli İstatistiksel Yöntemler, Ankara: Detay Yayıncılık.
9 Alpar, R. (2020). Uygulamalı İstatistik ve Geçerlik Güvenirlik, Ankara: Detay Yayıncılık.
Required Course instruments and materials

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

Student Work Load
Type of Work Weekly Hours Number of Weeks Work Load
Weekly Course Hours (Theoretical+Practice) 3 16 48
Outside Class
       a) Reading 3 10 30
       b) Search in internet/Library 2 10 20
       c) Performance Project 0
       d) Prepare a workshop/Presentation/Report 3 1 3
       e) Term paper/Project 4 2 8
Oral Examination 0
Quiz 0
Laboratory exam 3 2 6
Own study for mid-term exam 5 7 35
mid-term exam 2 1 2
Own study for final exam 5 7 35
final exam 3 1 3
0
0
Total work load; 190