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Course Information
Course Unit Title : Statistical applications in tourism research
Course Unit Code : 02TIS5129
Type of Course Unit : Optional
Level of Course Unit : Second Cycle
Year of Study : Preb
Semester : 255.Semester
Number of ECTS Credits Allocated : 6,00
Name of Lecturer(s) : ---
Course Assistants :
Learning Outcomes of The Course Unit : This course will compare and understand with more commonly used statistical procedures such as analysis of variance, multiple regression analysis, and factor analysis; This course will familiarize graduate students in psychology with the language, logic, and implementation of statiscal modeling
Mode of Delivery : Face-To-Face
Prerequisities and Co-requisities Courses : Unavailable
Recommended Optional Programme Components : Unavailable
Course Contents : This graduate course overviews the application of advance statiscal methods to various analysis problems confronted throughout the social, behavioral, and tourism sciences. Topics will include Spss program, using spss with measurement and multivariate models, reliability, vallidity, correlation,regression analyse, logistic regression, explorative factor analysis,chi-square and cluster analyse.
Languages of Instruction : Turkish
Course Goals : Advanced research in tourism is to have the ability to do statistical analysis.
Course Aims : The goal of this course is to have students able to construct, analyze, modify, and test the adequacy of variety of multivariate statiscal models using with spss and report the results of their analyses in a manner acceptable in refereed journals.
WorkPlacement  
Recommended or Required Reading
Textbook : Hair, Joseph F., et al. Multivariate data analysis. Vol. 6. Upper Saddle River, NJ: Pearson Prentice Hall, 2006.
Additional Resources : Cohen, Jacob, et al. Applied multiple regression/correlation analysis for the behavioral sciences. Routledge, 2013.
Material Sharing
Documents : Peng, Bo, Haiyan Song, and Geoffrey I. Crouch. "A meta-analysis of international tourism demand forecasting and implications for practice." Tourism Management 45 (2014): 181-193.
Assignments : Lecturing at the end of each one to analyze data by students
Exams :
Additional Material :
Planned Learning Activities and Teaching Methods
Lectures, Practical Courses, Presentation, Seminar, Project, Laboratory Applications (if necessary)
ECTS / Table Of Workload (Number of ECTS credits allocated)
Student workload surveys utilized to determine ECTS credits.
Activity :
Number Duration Total  
Course Duration (Excluding Exam Week) :
14 3 42  
Time Of Studying Out Of Class :
14 3 42  
Homeworks :
3 10 30  
Presentation :
2 20 40  
Project :
0 0 0  
Lab Study :
0 0 0  
Field Study :
0 0 0  
Visas :
2 10 20  
Finals :
1 10 10  
Workload Hour (30) :
30  
Total Work Charge / Hour :
0  
Course's ECTS Credit :
0      
Assessment Methods and Criteria
Studies During Halfterm :
Number Co-Effient
Visa :
1 40
Quiz :
0 0
Homework :
1 20
Attendance :
0 0
Application :
0 0
Lab :
0 0
Project :
0 0
Workshop :
0 0
Seminary :
1 40
Field study :
0 0
   
TOTAL :
100
The ratio of the term to success :
40
The ratio of final to success :
60
TOTAL :
100
Weekly Detailed Course Content
Week Topics  
1 Basic Concepts, An Overview of Statistical Methods
 
2 Normality, Reliablity and Validity
 
3 A general overview of parametric and non-parametric test
 
4 Chi-Square Analyse
 
5 Correlation Analyse
 
6 Simple Linear Regression Analysis and basic assumptions
 
7 Multiple Linear Regression Analysis
 
8 Mid-term
 
9 Multiple Linear Regression Analysis by Stepwise Method
 
10 Logistic Regression
 
11 Exploratory Factor Analysis
 
12 Discriminant Analyse
 
13 Cluster Analyse
 
14 Overall Assessment, Reporting and Implementation
 
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