Nevşehir Hacı Bektaş Veli University Course Catalogue
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| Year/Semester of Study | 1 / Fall Semester | ||||
| Level of Course | 2nd Cycle Degree Programme | ||||
| Type of Course | Compulsory | ||||
| Department | TOURISM TECHNOLOGIES AND INNOVATION (MASTER'S WITH THESIS) | ||||
| 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 | |||||
| Using statistical package program to analyze data and reporting the results. Students conduct survey research to learn research analysis techniques. Introducing the necessary tools to implement statistical methods and develop further the understanding of assumptions and limitations. | |||||
| Learning Outcomes | PO | MME | |
| The students who succeeded in this course: | |||
| LO-1 | Acknowledge the place and the importance of statistics in the field of social sciences . |
PO-1 Develops and implements innovative business models based on technology in the field of tourism. PO-2 It can use innovative research methods to collect big data, evaluate it and use it in decision processes. |
Examination Laboratory Exam Presentation Term Paper |
| LO-2 | Using statistical package program to learn data analysis. |
PO-1 Develops and implements innovative business models based on technology in the field of tourism. PO-2 It can use innovative research methods to collect big data, evaluate it and use it in decision processes. |
Examination Laboratory Exam Presentation Term Paper |
| LO-3 | Learn to conduct statistical methods and to comment solutions. |
PO-4 Understands and applies innovation-based marketing strategies in the field of tourism. PO-5 Can apply artificial intelligence approaches to tourism problems. |
Examination Laboratory Exam Presentation Term Paper |
| PO: Programme Outcomes MME:Method of measurement & Evaluation |
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| Course Contents | ||
| Basic Content of Statistics. Subject of statistics and basic concepts: unit, population and variable; definition and kinds of variables, scaling of variables and determination of scales. Collecting the data methods. Questionnaire survey method. Sampling. Introducing the statistical package program. Data entry, data definition. Graph and table introducing. Confidence intervals. Hypothesis tests. Correlation coefficient. Chi-square analysis. ANOVA. Regression Analysis. | ||
| Weekly Course Content | ||
| Week | Subject | Learning Activities and Teaching Methods |
| 1 | Basic Content of Statistics. | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 2 | Subject of statistics and basic concepts: unit, population and variable; definition and kinds of variables, scaling of variables and determination of scales. | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 3 | Data collection methods. Questionnaire survey method. Sampling. | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 4 | Introducing the statistical package program. Data entry, data definition. | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 5 | Plots and table introduction. | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 6 | Confidence intervals. | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 7 | Confidence intervals. | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 8 | mid-term exam | |
| 9 | Hypothesis tests. | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 10 | Chi-square analysis. | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 11 | Nonparametric tests | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 12 | ANOVA | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 13 | Correlation coefficients. | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 14 | Regression Analysis. | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 15 | Regression Analysis. | Representing subjects. Question and answer. Solving problems technique. Computer application. |
| 16 | final exam | |
| Recommend Course Book / Supplementary Book/Reading | ||
| 1 | “Bilimsel Araştırma Süreci ve SPSS İle Veri Analizi” A., URAL, İ., KILIÇ | |
| 2 | “SPSS Uygulamalı Çok Değişkenli İstatistik Teknikler” Editör: Doç. Dr. Şeref KALAYCI | |
| 3 | “Paket Programlar ile İstatistiksek Veri Analizi-I” Prof. Dr. Kazım ÖZDAMAR | |
| Required Course instruments and materials | ||
| Book, computer | ||
| Assessment Methods | |||
| Type of Assessment | Week | Hours | Weight(%) |
| mid-term exam | 1 | 2 | |
| Other assessment methods | |||
| 1.Oral Examination | |||
| 2.Quiz | |||
| 3.Laboratory exam | 2 | 2 | 0 |
| 4.Presentation | |||
| 5.Report | |||
| 6.Workshop | |||
| 7.Performance Project | 10 | 2 | |
| 8.Term Paper | 1 | 1 | 0 |
| 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 | 2 | 10 | 20 |
| c) Performance Project | 3 | 14 | 42 |
| d) Prepare a workshop/Presentation/Report | 1 | 10 | 10 |
| e) Term paper/Project | 3 | 1 | 3 |
| 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; | 177 | ||