國立高雄餐旅大學
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課程介紹 |
課程名稱: |
高等數量方法(觀光研究所碩士學分班-全英授課)
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縣 市: |
高雄市
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上課時間: |
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起始日期: |
2019/7/29
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結束日期: |
2019/8/8
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上課地點: |
國立高雄餐旅大學
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相關鏈結: |
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課程介紹: |
授課教師:Professor Dogan GursoyDr. Dogan Gursoy is the Taco Bell Distinguished Professor in Hospitality Business Management at Washington State University in the School of Hospitality Business Management and the editor of Journal of Hospitality Marketing & Management. He is also the developer and designer of the "Hotel Simulation" (http://www.hotelsimulation.com/), a virtual management training game where participants are divided into teams and assigned the task of running 500-room hotels in a competitive virtual marketplace. The Hotel Business Management Training Simulation has been used for both revenue management and hospitality management purposes by several institutions. Dr. Gursoy is recognized as one of the leading researchers in the hospitality and tourism area. His area of research includes sustainability, services management, hospitality and tourism marketing, tourist behavior, travelers' information search behavior, community support for tourism development, cross-cultural studies, consumer behavior, involvement and generational leadership. His research has been published broadly. His research has also been presented at numerous hospitality and tourism conferences and received numerous research awards. Dr. Gursoy has recently been recognized as one of the top 10 authors in the world in terms of publications in the top six hospitality/tourism journals during the past decade (Journal of Hospitality and Tourism Research (2011), 35(3), 381-416).
Research Interests:
Community Support For Tourism Development
Consumer Behavior
Cross Cultural Studies
Hospitality And Tourism Marketing
Information Search
Involvement And Generational Leadership
Services Management
Sustainability
Tourist Behavior
Travelers' Behaviors And Attitudes
Travelers' Information Search Behavior
偕同教師:梁榮達教授、王東昇助理教授Coordinator teacher:Professor Liang, Rong-Da & Assistant Professor Wang, Tung-Sheng
課程說明COURSE OVERVIEW
This course covers quantitative statistical techniques with an emphasis on applications for business, hospitality, marketing research and consumer behavior. The course is compares and contrast many different multivariate quantitative techniques. The course emphasizes applications of multivariate quantitative analysis from a conceptual viewpoint as well as research design.
This course is not intended to be a mathematical development of the theories underlying these statistics. Rather, the course is designed to provide students with an understanding of how and when to apply specific multivariate quantitative techniques to data. During the course, we will explore how to properly design a research project with its subsequent multivariate quantitative analyses in mind, how to choose the appropriate multivariate quantitative method, how to test the fundamental assumptions underlying various quantitative methods, and how to validate and evaluate a multivariate data analysis.
In addition to the above-stated goals, students will also learn how to implement these multivariate techniques on new/existing datasets using SPSS.
COURSE OBJECTIVES
To introduce different quantitative methods for multivariate data analysis
To explain how to match multivariate quantitative techniques with research objectives
To test the assumptions and interpret the results of multivariate output
To understand the issues in the estimation and validation of a multivariate quantitative analysis.
To understand research employing various quantitative techniques
To learn how to analyze & interpret multivariate quantitative statistical output from SPSS software package
TEXTBOOK
Multivariate Data Analysis, 7th edition by Joseph F. Hair, William C. Black, Barry J. Babin, Rolph E. Anderson, Prentice-Hall: Upper Saddle River, N.J., ISBN: 0138132631
SOFTWARE
We will be using IBM SPSS statistics software package in this class. Please make sure that you have access to the software.
COURSE ORGANIZATION AND REQUIREMENTS
The course will operate as student-centered seminar. The instructor will provide introductions to the course on particular topics, and will also present additional substantive material as appropriate. Students are encouraged to find additional readings on the topic in question.
Quizzes
There are 3 quizzes given over the semester. The quizzes are designed to enhance and reward the mastery of the material from the textbook and class sessions. Quizzes usually emphasize recent lectures but quizzes can contain past material as well. There are no make-up quizzes.
Exercises
Exercise assignments involve collecting/entering raw data, conducting the appropriate statistical analysis and writing short reports of those analyses. Not all class assignments are pre-scheduled on the syllabus. I reserve the right to give an assignment in class that does not appear in the syllabus. Assignments will be given out to students during class and will be due at the beginning of the following scheduled class. If a student misses a class, it is his/her responsibility to obtain the assignment from the instructor or another student. I usually review the assignments in class the day they are due, so absolutely no late class assignments will be accepted.Short Paper
Short paper is intended to show students’ competency in writing up quantitative statistical results. Short paper should describe the results obtained from applying a quantitative technique to appropriate data of your choice. The assumptions and purposes of the techniques should be made clear. Short paper represents individual work. The data for use in a short paper may be individually collected by the student or may be existing data from a reliable source (please check with instructor for approval to use outside data sources). In addition, short papers should be fresh analyses (not write-ups of master’s/doctoral/previous analyses).
Short-papers should be no more than 5 pages each (not including the computer analysis output or appendices). Short paper must be based on any technique discussed in class. If you have questions about what constitutes a short paper, please ask the instructor. Please see the late assignment policy for late submission penalty.
Paper Presentation & Critique
You have 2 paper presentation and critique due this semester. The purpose of this assignment is to apply your knowledge of multivariate analysis to understand and evaluate a research study published in the professional literature in your area. You should find at least one article published within the last 5 years (must be a 2013 article or later) in a top refereed journal in your area of study that uses one or more of the multivariate techniques discussed in this course. You must obtain approval from the Instructor for the paper. You also must include a copy of the original article(s) with your final presentation. (If you choose to critique more than one article, please include a compare/contrast section.)
The assignment involves an oral presentation of the article with PowerPoint, the technique(s) used in the article and a critique of the overall paper. The presentation should summarize and evaluate the following aspects of the article:
Stated objectives of the article
Research design & data collection
Selection of the multivariate technique (were assumptions met?)
Estimation and assessment of overall model fit
Interpretation of the results & validity implications
Suggestions for improvement (design, data collection, and/or analysis)
Please submit an electronic copy of your PowerPoint presentation and original article (if possible) to the instructor. You also must bring a printed handout of your presentation to give out to the entire class on the day you present. No late presentations are allowed. LATE WORK POLICY
Late work is not routinely accepted. In extenuating circumstances, it may be accepted with substantial penalty.
A late submission penalty of 25% for the first day and 10% per day after the first day (seven days a week) will be assessed to all assignments & documents not handed in on time. Assignments more than two weeks late will not be accepted for credit. No assignment will be accepted after the last day of class.
ACEDEMIC INTEGRITY
Academic integrity will be strongly enforced in this course. Any student caught cheating on any assignment will be given an F for the course.
I encourage you to work with classmates on assignments. However, each student must turn in original work. No copying will be accepted. Students who violate this policy will receive an F as a final grade in this course.
Any student who attempts to gain an unfair advantage over other students by cheating, will fail the course. You must do your own work.
STUDENT EVALUATION AND GRADING
30%
The quizzes are given at the beginning of class. A missed quiz receives zero points. There are NO make-up quizzes!
10%
Exercises involving the estimation of a quantitative model on a dataset, obtaining the results and interpreting those results. Each exercise is pass-fail.
20%
You will need to write a short paper. Your paper will describe the results obtained from applying a quantitative technique to appropriate data of your choice.
10%
The presentation of the short papers
20%
You will critique at least two articles. An article critique that provides an approximately 5 page (double-spaced) review of the statistical analysis in a published article in a respected scholarly journal. The article must include an analysis employing one of the statistical techniques covered in the course.
10%
The presentation of the critique
Grading Scale
940-1,000 points A
900-939 A-
870-899 B+
830-869 B
800-829 B-
770-799 C+
730-769 C
700-729 C-
670-699 D+
600-669 D
0-599 F
COURSE ORGANIZATION AND REQUIREMENTS
The course will operate as a seminar class. Students will be assigned readings each week and asked to lead the discussion of that reading.
*Teach 5 hours a day. Two hours in the morning and three hours in the afternoon.
Date
Chapter
Section One -- Preparing to Apply Multivariate Analysis
1
July 29
10-12; 13-16
Overview of Multivariate Methods
Examining Your Data & Multivariate Relationships
Section Two -- Dependence Techniques
2
July 30
10-12; 13-16
Multiple Regression Analysis
Quiz 1
3
July 31
10-12; 13-16
Multiple Discriminant Analysis
Article Critique Presentation 1
4
August 1
10-12; 13-16
Canonical Correlation Analysis
Article Critique Presentation 2
5
August 2
10-12; 13-16
MANOVA and GLM
Article Critique Presentation 3
Weekend - No class
6
August 5
10-12; 13-16
Conjoint Analysis
Article Critique Presentation 4
Section Three -- Interdependence Techniques
7
August 6
10-12; 13-16
Exploratory Factor Analysis
Article Critique Presentation 5
Quiz 2
8
August 7
10-12; 13-16
Cluster Analysis
Multidimensional Scaling
Article Critique Presentation 6
9
August 8
10-12; 13-16
Confirmatory Factor Analysis
Structural Equation Modeling
Article Critique Presentation 7
Quiz 4
Short Paper 2 Due
Short paper presentations
Weekend - No class
※ 協同教師:梁榮達教授、王東昇助理教授
Coordinator teacher:Professor Liang, Rong-Da & Assistant
Professor Wang, Tung-Sheng
※ Professor Dogan Gursoy Timetable授課時間(45hrs):
7/29-8/2:1000-1200、1300-1600
8/5-8/8:1000-1200、1300-1600
※ Professor Liang, Rong-Da & Assistant Professor Wang, Tung-Sheng
Timetable(tentative)
梁榮達教授、王東昇助理教授暫定上課時間(9hrs):
7/29-8/2:1600-1700
8/5-8/9:1600-1700
※ 學分數Academic Credit:3學分
Theregistrationof foreign students for the courseForeign students please download the registration form, and e-mail to cec@mail.nkuht.edu.tw afterthe registration form is completed.Download the registration form.
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812 高雄市小港區松和路1號
國立高雄餐旅大學 推廣教育中心。
親臨繳費:
週一至週五上班時間AM9:00-PM5:00至本校第二實習大樓6樓繳費(開課當日恕不接受現場繳費)。
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報名繳費後,因不可抗力之因素(需提出證明),得於一定期限內請求退費。
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完成報名手續至開課前退費者:退還應繳金額之90%
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備註
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烘焙相關課程:請學員需自備磅秤、半圓刮片、擠花袋(18吋)、打蛋器(12吋)、桿麵棍(30cm)、橡皮刮刀、木柄抹刀、平口花嘴工具,以利課程進行。
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教學內容: |
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師資介紹: |
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備 註: |
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學分班註記: |
否
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學分數: |
0.0
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課程時數: |
54.0
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課程狀態: |
不開班
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上架日期: |
2019/1/31 下午 02:36:57
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更新日期: |
2020/3/30 下午 03:48:10
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上課地點 |
名 稱: |
國立高雄餐旅大學
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簡 介: |
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地 址: |
高雄市小港區松和路一號
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電 話: |
07-8060505#18200-18206
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傳 真: |
07-8032534
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連絡人: |
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email: |
cec@mail.nkuht.edu.tw
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