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Information
| Unit | INSTITUTE OF NATURAL AND APPLIED SCIENCES |
| AGRICULTURAL ECONOMICS (MASTER) (WITH THESIS) | |
| Code | TE553 |
| Name | Applications of Multivariate Anaysis in Economic and Social Research |
| Term | 2018-2019 Academic Year |
| Term | Fall |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Dr. Öğr. Üyesi TUNA ALEMDAR |
| Course Instructor |
The current term course schedule has not been prepared yet.
|
Course Goal / Objective
Dimension reduction in multivariate data sets in economic and social researches, examining interdependency structure among data, classification of observations and variables, conducting statistical tests
Course Content
Exploratory and confirmatory mutltivariate statistical analyses;relations and variables; categorical variables; dimension reduction in data; techniques of grouping and classifying; main multivariate analysis techniques; principal components analysis; factor analysis, discriminant analysis, cluster analysis, correspondence analysis, multiple regression analysis, canonical corelation, multidimensional scaling, structural equations modelling and applications of other multidimensional analyses and interpreting analysis results
Course Precondition
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Be able to describe main concepts, theories and methods used in multivariate statistical analyses |
| LO02 | to be able to determine the most appropriate multivariate analysis technique for various research problems |
| LO03 | to be able to apply main multivariate research methods in economic and social fields, to be able to get use of appropriate software and to interprete the results |
| LO04 | to be able to critically interprete scientific articles written on actual problems of economic and social sciences under the light of the knowledge acquired from multivariate analysis methods |
| LO05 | to be able to transfer results of multivariate analyses to others by using verbal, written and visual tools |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | - | Able to further develop and deepen knowledge acquired based on the undergradute level proficiencies in the fields of farm management and agricultural policy | |
| PLO02 | - | Able to comprehend interactions among related disciplines and field of agricultural economics | |
| PLO03 | - | Able to use theoretical and practical knowledge of agricultural economics in their specialization area | |
| PLO04 | - | Able to prepare reports on developments in national economy and agricultural sector; able to critically evaluate historical and actual developments in agriculture and economy; able to observe and interpret economics related publications | |
| PLO05 | - | Able to use software widely used in agricultural economics | |
| PLO06 | - | Able to combine data of actual developments with his knowledge, data and findings obtained in various disciplines and interpret them while supporting them with qualitative and quantitative data and also forming new knowledge through synthesis | |
| PLO07 | - | Ability to take the lead in multidisciplinary teams and work in teams | |
| PLO08 | - | Able to critically evaluate specialized knowledge and abilities acquired in agricultural economics and direct his/her own learning process | |
| PLO09 | - | Constantly adapt himself to new scientific developments | |
| PLO10 | - | Able to use acquired and digested agricultural economics knowledge in multidisciplinary studies, able to explain them, to transfer them to others, able to examine conclusions critically | |
| PLO11 | - | Able to transfer research results using verbal, written and visual tools | |
| PLO12 | - | Able to collect data according to scientific methods in order to solve economic problems, able to supervise and interprete data collected while taking into consideration social, scientific and ethical values | |
| PLO13 | - | Able to develop analytical approaches in order to solve complicated problems that cannot be forecast beforehand in applications of agricultural economics and policy; able to design research process; able to produce solutions by taking on responsibility and to evaluate and justify solutions |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Data types, classification of multivariate analysis methods | Lecture notes and suggested resources | |
| 2 | Data preparation for multivariate analyses, check for normality, concept of multivariate normality | Lecture notes and suggested resources | |
| 3 | Correlation, partial correlation | Lecture notes and suggested resources | |
| 4 | Principle Components Analysis, difference from factor analysis | Lecture notes and suggested resources | |
| 5 | Factor analysis, exploratory and confirmatory factor analyses, factor scores, matrix rotations, application areas | Lecture notes and suggested resources | |
| 6 | Cluster Analysis | Lecture notes and suggested resources | |
| 7 | Discriminant Analysis | Lecture notes and suggested resources | |
| 8 | Mid-Term Exam | Lecture notes and suggested resources | |
| 9 | Multiple regression and logistic regression analyses | Lecture notes and suggested resources | |
| 10 | Multidimensional Analysis of Variance (MANOVA); t tests; comparion of ANOVA with MANOVA | Lecture notes and suggested resources | |
| 11 | Canonical Correlation; Multidimensional Scaling | Lecture notes and suggested resources | |
| 12 | CorrespondenceAnalysis | Lecture notes and suggested resources | |
| 13 | Conjoint Analysis | Lecture notes and suggested resources | |
| 14 | Introduction to Structural Equation Models | Lecture notes and suggested resources | |
| 15 | General Overview | Lecture notes and suggested resources | |
| 16 | Term Exams | Lecture notes and suggested resources | |
| 17 | Term Exams | Lecture notes and suggested resources |