PSY214 Applied Statistics

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Course Code Course Title Weekly Hours* ECTS Weekly Class Schedule
T P
PSY214 Applied Statistics 3 0 6
Prerequisite None It is a prerequisite to

None

Lecturer Pınar Ünal-Aydın Office Hours / Room / Phone
Monday:
10:00-12:00
Tuesday:
10:00-12:00
Wednesday:
10:00-11:00
B F2.7C
E-mail paydin@ius.edu.ba
Assistant Assistant E-mail
Course Objectives Aquire general principles of scientific thinking Develop basic statistical concepts and skills Evaluate statistical data in research reports Visually communicate statitical results Apply statistics in psychology
Textbook Gravetter, F. J., & Wallnau, L. B. (2034). Statistics for the behavioral sciences (9th ed.). Belmont, CA: Wadsworth. (ISNB: 1-111-83099-1) + Supplementary Readings
Learning Outcomes After successful  completion of the course, the student will be able to:
    Teaching Methods Class lectures, discussions, and exercises will be held online. Active tutorial sessions for engaged learning and feedback on progress. Assessment of outcomes will involve assignments, six quizzes, midterm exam, and final exam.
    WEEK TOPIC REFERENCE
    Week 1 Course scope and review exercises Ch 1, 9
    Week 2 Introduction to the t-statistic Ch 9
    Week 3 t-test for independent samples (Q#1) Ch 10
    Week 4 t-test for dependent samples Ch 11
    Week 5 Introduction to Analysis of Variance (Q#2) Ch 12
    Week 6 Repeated measures Analysis of variance Ch 13
    Week 7 Two-factor Avalysis of Variance (Q#3) Ch 14
    Week 8 MIDTERM EXAM Ch 15
    Week 9 Correlation Ch 16
    Week 10 Introduction to regression (Q#4) Ch 17
    Week 11 Chi-square statistic Ch 18
    Week 12 Binomial test (Q#5) Ch 19
    Week 13 Non-parametric tests, confidence intervals, effect sizes, power, meta analysis Ch 20
    Week 14 Review (Q#6)
    Week 15 Review
    Assessment Methods and Criteria Evaluation Tool Quantity Weight Alignment with LOs
    Final Exam 1 30
    Semester Evaluation Compenents
    ***     ECTS Credit Calculation     ***
     Activity Hours Weeks Student Workload Hours Activity Hours Weeks Student Workload Hours
    Lecture Hours 2 14 28 ın term study 10 1 10
    assignments 1 6 6 final exam 15 2 30
    active tutorials 1 12 12 quizzes 6 6 36
    home study 2 14 28 home study 2 14 28
            Total Workload Hours = 178
    *T= Teaching, P= Practice ECTS Credit = 6
    Course Academic Quality Assurance: Semester Student Survey Last Update Date: 06/11/2020
    QR Code for https://ecampus.ius.edu.ba/syllabus/psy214-applied-statistics

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