Nevşehir Hacı Bektaş Veli University Course Catalogue

Information Of Programmes

TOURISM RESEARCH INSTITUTE / GMS604 - GASTRONOMY AND CULINARY ARTS (DOCTORATE DEGREE)

Code: GMS604 Course Title: MULTI-VARIABLE STATISTICS ANALYSIS 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 GASTRONOMY AND CULINARY ARTS (DOCTORATE DEGREE)
Pre-requisities and Co-requisites None
Mode of Delivery Face to Face
Teaching Period 14 Weeks
Name of Lecturer BEKİR BORA DEDEOĞLU (b.bora.dedeoglu@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-2 Gastronomy and Culinary Arts in the field of businesses to analyze the problems and have the ability to solve problems.
PO-6 Gastronomy and Culinary Arts with the ability to evaluate information in a critical way.
PO-7 Gastronomy and Culinary Arts in the field of applications of social, scientific and ethical values to have the competence to see.
Examination
Laboratory Exam
Presentation
LO-2 design and conduct experiments as well as to analyze and interpret data PO-1 Develops and deepens the knowledge and skills of Gastronomy and Culinary Arts and related disciplines at the level of expertise.
PO-2 Gastronomy and Culinary Arts in the field of businesses to analyze the problems and have the ability to solve problems.
PO-7 Gastronomy and Culinary Arts in the field of applications of social, scientific and ethical values to have the competence to see.
Examination
Laboratory Exam
Presentation
LO-3 identify, formulate and solve real life problems PO-2 Gastronomy and Culinary Arts in the field of businesses to analyze the problems and have the ability to solve problems.
PO-7 Gastronomy and Culinary Arts in the field of applications of social, scientific and ethical values to have the competence to see.
PO-3 Have professional techniques and practices related to Gastronomy and Culinary Arts activities.
Examination
Laboratory Exam
Presentation
LO-4 Usage of statistical package program and software knowledge to solve real life problems PO-2 Gastronomy and Culinary Arts in the field of businesses to analyze the problems and have the ability to solve problems.
PO-6 Gastronomy and Culinary Arts with the ability to evaluate information in a critical way.
PO-7 Gastronomy and Culinary Arts in the field of applications of social, scientific and ethical values to have the competence to see.
Examination
Laboratory Exam
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 Data analysis and types Representing subjects. Question and answer. Solving problems technique.
2 Descriptive Statistics Normal Distribution Assumption Representing subjects. Question and answer. Solving problems technique. Computer application.
3 Factor Analysis Reliability Analysis Representing subjects. Question and answer. Solving problems technique. Computer application.
4 t-tests (Independent two-sample t-test, Dependent two-sample t-test, One-sample t-test) Representing subjects. Question and answer. Solving problems technique. Computer application.
5 One-way and factorial analysis of variance Representing subjects. Question and answer. Solving problems technique. Computer application.
6 Non-parametric tests Representing subjects. Question and answer. Solving problems technique. Computer application.
7 Quiz 1 Question and answer. Computer application.
8 mid-term exam
9 One-way and factorial multivariate analysis of variance Representing subjects. Question and answer. Solving problems technique. Computer application.
10 Covariance and multivariate covariance analysis Representing subjects. Question and answer. Solving problems technique. Computer application.
11 Correlation, Regression (Linear and multiple linear) Representing subjects. Question and answer. Solving problems technique. Computer application.
12 Application of regression analysis with mediating variable (Mediation Model) Representing subjects. Question and answer. Solving problems technique. Computer application.
13 Applying regression analysis with moderating variable (Moderation Model) Question and answer. Computer application. Student presentation.
14 Quiz 2 Question and answer. Computer application.
15 Quiz 3 Question and answer. Computer application.
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 Kalaycı, Ş. (2008). SPSS Uygulamalı Çok Değişkenli İstatistik Teknikler. Asil Yayın Dağıtım: Ankara.
3 Altunışık, R., Coşkun, R., Bayraktaroğlu, S. ve Yıldırım, E. (2007). Sosyal Bilimlerde Araştırma Yöntemleri. Sakarya: Sakarya 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 0
       b) Search in internet/Library 3 10 30
       c) Performance Project 2 8 16
       d) Prepare a workshop/Presentation/Report 0
       e) Term paper/Project 3 1 3
Oral Examination 4 1 4
Quiz 0
Laboratory exam 0
Own study for mid-term exam 3 2 6
mid-term exam 5 7 35
Own study for final exam 5 7 35
final exam 3 1 3
0
0
Total work load; 180