Faculty of Humanities and Social Sciences · Psychology · Undergraduate
Course Objective
The aim of this course is to enable students to comprehend fundamental statistical concepts, types of distributions, measures of central tendency and variability, normal distribution, hypothesis testing, and basic parametric and non-parametric tests, and to interpret this knowledge within the context of scientific research. Students will develop statistical thinking skills and gain basic competencies in analyzing and interpreting data.
Course Content
This course covers the fundamental concepts of statistics, including the definitions of population, sample, and statistics. It introduces different types of variables, levels of measurement, and scale types. Students learn how to organize data using frequency distributions and how to represent data with various types of graphs. The course also includes measures of central tendency such as mean, median, and mode, as well as measures of variability including range, quartiles, percentiles, mean absolute deviation, variance, standard deviation, and coefficient of variation.
Further topics include the characteristics of the normal distribution, the concept of linearity, and the transformation of raw scores into standard scores (z-scores). The course also explains the logic of hypothesis testing, including null and alternative hypotheses, and explores related concepts such as Type I and Type II errors, degrees of freedom, and confidence intervals. Finally, students are introduced to basic parametric and non-parametric statistical tests and their appropriate usage in data analysis.
Required Resources
Gravetter, F. J., & Wallnau, L. B. (2017). Statistics for the behavioral sciences (10th ed.). Cengage Learning.
Howell, D. C. (2013). Statistical methods for psychology (8th ed.). Wadsworth.
Recommended Resources
Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). Pearson
Field, A. (2018). Discovering statistics using IBM SPSS statistics (5th ed.). SAGE Publications.
Course Learning Outcomes
- Defines basic statistical concepts
- Layouts datas.
- Draws the frequency graph
- Calculates central tendency measures
- Determines the distribution of the central tendency measures according to their size
- Interprets and accounts for change measures
- To be able to collect data for specific problems using correct sampling methods.
- To be able to explain the purpose of descriptive and inductive methods in applications.
- To be able to transfer data to graphical form and interpret them.
- The ability to analyze hypothesis tests and Type I and Type II errors in an applied context.
- Evaluating the assumptions of normal distribution and parametric tests.
- The ability to perform basic statistical analyses using SPSS software.
Core Area Distribution
Teaching Methods
Assessment & Evaluation
ECTS / Workload
| Activity | Quantity | Duration (h) | Total Workload |
|---|---|---|---|
| Course Duration (Including Exam Week) | 16 | 3 | 48 |
| Out of Class Study Period | 16 | 2 | 32 |
| Midterm | 1 | 20 | 20 |
| Quiz | 0 | 0 | 0 |
| Assignment | 0 | 0 | 0 |
| Practice | 10 | 3 | 30 |
| Final | 1 | 30 | 30 |
Course Schedule
| Week | Subject | Preparation |
|---|---|---|
| 1 | Basic Statistical Concepts (Population, Sample, Statistics) | Lecture Notes |
| 2 | Basic Statistical Concepts (Types of Variables, Measurement, and Scale Types) | Lecture Notes |
| 3 | Frequency Distributions and Graphs | Lecture Notes |
| 4 | Measures of Central Tendency (Mean, Mode, Median) | Lecture notes |
| 5 | Measures of Dispersion (Range, Quartiles and Percentiles, Mean Absolute Deviation) | Lecture notes |
| 6 | Measures of Dispersion (Variance, Standard Deviation, Coefficient of Variation) | Lecture notes |
| 7 | General Review | Lecture notes |
| 8 | Midterm Exam | Midterm Exam |
| 9 | Normal Distribution and Linearity | Lecture notes |
| 10 | Normal Distribution and Score Transformations | Lecture notes |
| 11 | Hypothesis Testing | Lecture notes |
| 12 | Type I and Type II Errors, Degrees of Freedom, Confidence Intervals | Lecture notes |
| 13 | Parametric Tests | Lecture notes |
| 14 | Non-parametric Tests | Lecture notes |
| 15 | General Review | Lecture notes |
| 16 | Final Exam | Final Exam |


