Nevşehir Hacı Bektaş Veli University Course Catalogue
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| Year/Semester of Study | 1 / Spring Semester | ||||
| Level of Course | 2nd Cycle Degree Programme | ||||
| Type of Course | Compulsory | ||||
| Department | TOURISM GUIDING (PHD) | ||||
| 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 | Application of Multivariate Statistical Analysis techniques is learned. |
PO-4 Has advanced knowledge of quantitative and qualitative research methods. PO-5 Has detailed information about statistical analysis types. |
Examination Laboratory Exam Presentation |
| LO-2 | Ability to analyze, evaluate, experiment and design data |
PO-4 Has advanced knowledge of quantitative and qualitative research methods. PO-5 Has detailed information about statistical analysis types. |
Examination Laboratory Exam Presentation |
| LO-3 | Ability to use statistical software and solve real-life problems |
PO-5 Has detailed information about statistical analysis types. PO-6 Knows and applies scientific ethical rules PO-7 Plans, conducts, analyzes and reports a scientific research |
Examination Laboratory Exam Presentation |
| PO: Programme Outcomes MME:Method of measurement & Evaluation |
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| 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. Computer application. |
| 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 | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 14 | Confirmatory factor analysis | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 15 | Structural equation modeling | Representing subjects. Question and answer. Solving problems technique. 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. | |
| Required Course instruments and materials | ||
| Book, article, projection, internet resource, lecture notes | ||
| 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 | ||