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COURSE UNIT TITLECOURSE UNIT CODESEMESTERTHEORY + PRACTICE (Hour)ECTS
ADVANCED STATISTICAL APPLICATIONS PSK411 --------------- 3 + 0 4

TYPE OF COURSE UNITElective Course
LEVEL OF COURSE UNITBachelor's Degree
YEAR OF STUDY-
SEMESTER---------------
NUMBER OF ECTS CREDITS ALLOCATED4
NAME OF LECTURER(S)-
LEARNING OUTCOMES OF THE COURSE UNIT At the end of this course, the students;
1) Will learn the fundamental topics in multivariate statistics.
2) Will select appropriate analyses for the research questions that they confronted with.
3) Will use statistical packages to make multivariate statistics.
4) Will be able to write statistical reports of multivariate analyses.
5) Will design research questions suitable to multivariate analyses.
MODE OF DELIVERYFace to face
PRE-REQUISITES OF THE COURSENo
RECOMMENDED OPTIONAL PROGRAMME COMPONENTNone
COURSE CONTENTS
WEEKTOPICS
1st Week Introduction to Multivariate Statistics
2nd Week Data Screening
3rd Week Multiple Regression
4th Week Multiple Regression (continued)
5th Week Canonical Correlation
6th Week Multiway Frequency Analysis
7th Week Analysis of Covariance
8th Week Mid-term and Multivariate Analysis of Variance
9th Week Multivariate Analysis of Variance (continued)
10th Week Principal Component Analysis
11th Week Principal Component Analysis (continued)
12th Week Introduction to Structural Equation Modeling
13th Week Introduction to Structural Equation Modeling (continued)
14th Week Summing Up
RECOMENDED OR REQUIRED READINGTabachnick, B. G., & Fidell, L. S. (2011). Multivariate statistics. Boston: Allyn and Bacon.
PLANNED LEARNING ACTIVITIES AND TEACHING METHODSLecture,Discussion,Questions/Answers
ASSESSMENT METHODS AND CRITERIA
 QuantityPercentage(%)
Mid-term140
Total(%)40
Contribution of In-term Studies to Overall Grade(%)40
Contribution of Final Examination to Overall Grade(%)60
Total(%)100
LANGUAGE OF INSTRUCTIONTurkish
WORK PLACEMENT(S)No
  

KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
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