Psychology | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code: | PSI038 | ||||
Course Name: | Statistical Applications in Psychology | ||||
Semester: |
Fall Spring |
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Course Credits: |
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Language of instruction: | Turkish | ||||
Course Condition: | |||||
Does the Course Require Work Experience?: | No | ||||
Type of course: | Departmental Elective | ||||
Course Level: |
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Mode of Delivery: | Face to face | ||||
Course Coordinator: | Dr. Öğr. Üy. EMRE ÜNVER | ||||
Course Lecturer(s): | Asst. Prof. Halil Duzcu | ||||
Course Assistants: |
Course Objectives: | This course aims to teach basic concepts, variable types, preparing data for the statistical analysis, frequency distributions, central tendency, normal distribution, z scores, hypothesis testing, introduction to t test and correlation, analysis of variance |
Course Content: | Basic concepts and the function of statistics in psychology, the use of statistical tools for analyzing psychological data, and the connection between research designs and statistical analysis will be discussed in this course. |
The students who have succeeded in this course;
1) learning about the connection between data and research designs 2) learning the pre-analysis steps 3) choosing the appropriate analysis technique for a given research design 4) learning the statistical analyses such as correlation, t-test, Anova etc. |
Week | Subject | Related Preparation |
1) | Introduction to the variables – SPSS introduction | |
2) | Describing Data using Distributions and Graphs | |
3) | Measures of Central Tendency and Spread – Descriptive Statistics in SPSS | |
4) | Z-scores and Normal Distribution | |
5) | Hypothesis Testing – Independent t -test | |
6) | Hypothesis Testing – one sample t test and dependent t -test | |
7) | midterm | |
8) | Parametric Correlations | |
9) | Non-Parametric Correlations | |
10) | Analysis of Variance – One-way ANOVA | |
11) | Analysis of Variance – -Repeated Measures ANOVA | |
12) | Planned Contrasts and post-hoc tests | |
13) | Introduction to the Regression Analysis | |
14) | multiple regression models | |
15) | Final |
Course Notes / Textbooks: | Howell, D. C. (2012). Psikoloji için İstatistiksel metotlar. 8.Baskı, Cengage Learning. |
References: | An Introduction to Psychological Statistics, Foster et al. 2018 Open Resource: https://irl.umsl.edu/oer/4/ Demir, I. 2020. SPSS ile İstatistik REhberi, Efe Akademi, İstanbul |
Course Learning Outcomes | 1 |
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3 |
4 |
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Program Outcomes | ||||||||||||||
1) Have the theoretical knowledge in major sub areas of psychology. | 1 | |||||||||||||
2) Apply psychological consepts and theories in a variety of applied settings | 1 | 1 | ||||||||||||
3) Identify and explain the cognitive, emotional and behavioral processes of human. | 1 | |||||||||||||
4) Evaluate evidence and assumptions in a scientific and critical view. | 2 | |||||||||||||
5) Collect and analyze the research data and report the findings in accordance to ethical publication rules. | 3 | 3 | 3 | |||||||||||
6) Develop and utilize measurement tools for psychological phenomena. | 2 | 3 | ||||||||||||
7) Have the skills and abilities to follow advances in psyhology and other related sciences. | 1 | |||||||||||||
8) Have the skills and abilities to work effectively on individual and group based. | 3 | 3 | 3 | |||||||||||
9) Have the skills and abilities to communicate in a clear and effective manner in national and international settings. | 1 | |||||||||||||
10) Behave in accordance to the professional code of ethics applied to psychology. | 1 | 1 | 1 | 1 | ||||||||||
11) Be unprejudiced and equal to various identity groups based on such as age, gender, language, race, religion and social class in scientific and professional acitivities. | 1 | |||||||||||||
12) Have enhanced awareness of universal values as well as human and animal rights. | 1 | |||||||||||||
13) Master a foreign language at least B1 level of European Language Portfolio. | 2 | 2 | ||||||||||||
14) Master the computer softwares within information and communication technologies at least European computer driving licence. | 2 | 3 | 3 |
No Effect | 1 Lowest | 2 Average | 3 Highest |
Program Outcomes | Level of Contribution | |
1) | Have the theoretical knowledge in major sub areas of psychology. | 1 |
2) | Apply psychological consepts and theories in a variety of applied settings | 2 |
3) | Identify and explain the cognitive, emotional and behavioral processes of human. | 1 |
4) | Evaluate evidence and assumptions in a scientific and critical view. | 1 |
5) | Collect and analyze the research data and report the findings in accordance to ethical publication rules. | 3 |
6) | Develop and utilize measurement tools for psychological phenomena. | 2 |
7) | Have the skills and abilities to follow advances in psyhology and other related sciences. | 1 |
8) | Have the skills and abilities to work effectively on individual and group based. | 3 |
9) | Have the skills and abilities to communicate in a clear and effective manner in national and international settings. | 1 |
10) | Behave in accordance to the professional code of ethics applied to psychology. | 2 |
11) | Be unprejudiced and equal to various identity groups based on such as age, gender, language, race, religion and social class in scientific and professional acitivities. | 1 |
12) | Have enhanced awareness of universal values as well as human and animal rights. | 1 |
13) | Master a foreign language at least B1 level of European Language Portfolio. | 1 |
14) | Master the computer softwares within information and communication technologies at least European computer driving licence. | 2 |
Semester Requirements | Number of Activities | Level of Contribution |
Midterms | 1 | % 40 |
Final | 1 | % 60 |
total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 40 | |
PERCENTAGE OF FINAL WORK | % 60 | |
total | % 100 |
Activities | Number of Activities | Preparation for the Activity | Spent for the Activity Itself | Completing the Activity Requirements | Workload | ||
Course Hours | 13 | 0 | 3 | 39 | |||
Midterms | 1 | 0 | 36 | 36 | |||
Final | 1 | 0 | 50 | 50 | |||
Total Workload | 125 |