Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS CreditsLast Updated Date
2PSY 508Statistics in Clinical Psychology2+2+03801.08.2024

 
Course Details
Language of Instruction Turkish
Level of Course Unit Master's Degree
Department / Program MA Program in Clinical Psychology (Thesis) (%30 English)
Type of Program Formal Education
Type of Course Unit Compulsory
Course Delivery Method Face To Face
Objectives of the Course This is an introductory course in statistics that fits for students in a wide variety of areas of study. Various statistical concepts and intermediate statistical techniques including correlation, regression, confidence intervals, mean comparisons, hypothesis testing will be the focus of the course. Students also have the opportunity to analyze data sets using appropriate software programs.
Course Content Topics discussed throughout the course include displaying and describing data, survey and experimental designs, the normal distribution, correlation, regression, probability, sampling distribution, confidence intervals, mean comparisons, hypothesis testing and inferences.
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator None
Name of Lecturers Asist Prof.Dr. Lokman AKBAY
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources Keppel, G. (1991). Design and analysis: A researcher's handbook. Prentice-Hall, Inc.
Course Notes Coladarci, T., Cobb, C. D., Minium, E. W., & Clarke, R. B. (2004). The Fundamentals of Statistical Reasoning in Education. John Wiley & Sons, Inc.
Documents Coladarci, T., Cobb, C. D., Minium, E. W., & Clarke, R. B. (2004). The Fundamentals of Statistical Reasoning in Education. John Wiley & Sons, Inc.
Assignments In class discussions and participation (no submission needed) will also be graded toward the final grade
Exams İki tane ara sınav ve bir final sınavı yapılacaktır. Tüm sınavlar açık uçlu ve çoktan seçmeli madde tipleri başta olmak üzere farklı madde tipleri içerecektir.

Course Category
Mathematics and Basic Sciences %30
Social Sciences %40
Education %30

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 2 % 40
Quizzes 2 % 20
Attendance 1 % 10
Final examination 1 % 30
Total
6
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 2 28
Hours for off-the-c.r.stud 14 7 98
Mid-terms 2 25 50
Practice 14 2 28
Final examination 1 36 36
Total Work Load   Number of ECTS Credits 8 240

 
Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Develop skills on displaying and cleaning the data
2 Develop a theoretical understanding of the probability and normal curve
3 Understand theory of the mean comparison and hypothesis testing
4 Develop a theoretical understanding of concept of correlation and basic regression models
5 Analyze various datasets using related statistical software programs such as SPSS and interpret the analysis results

 
Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Displaying Data, Bar Chart, Histogram; Descriptive Statistics and Scatter Plots Coladarci et al, Chapters 1 & 2
2 Normal Distribution Coladarci et al, Chapters 3
3 Correlation Coladarci et al, Chapter 4
4 Linear Regression Coladarci et al, Chapter 5
5 Midterm Examination I
6 Contingency table and Chi-square testing Coladarci et al, Chapter 6
7 Probability Theory Coladarci et al, Chapters 12 & 13
8 Binomial Distribution Coladarci et al, Chapter 14
9 Sampling distribution models & Confidence interval Coladarci et al, Chapters 15 & 16
10 Midterm Examination II
11 Hypothesis testing; one sample z-test; t-distribution and one sample t-test Coladarci et al, Chapters 17, 18, & 20
12 Independent samples t-test and repeated measures Coladarci et al, Chapter 21
13 Inference for one & two proportions Coladarci et al, Chapters 22 & 23
14 ANOVA: One-way and factorial design Keppel, G. Chaptesrs 5 & 6
15 Final Examination

 
Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9
C1
C2
C3
C4
C5

  Contribution: 1: Very Slight 2:Slight 3:Moderate 4:Significant 5:Very Significant

  
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