1. Demonstrate a solid understanding of fundamental statistical concepts, including probability theory, descriptive statistics, hypothesis testing, and basic inferential techniques. 2. Formulate research questions and generate testable hypotheses relevant to real-world problems in social science research. 3. Design and execute simple experiments, collect data, and apply appropriate statistical techniques to analyze and interpret the results. 4. Develop proficiency in using statistical software for data management, visualization, and analysis, as well as interpreting the output generated by the software. 5. Critically evaluate and assess the validity of statistical analyses and conclusions in scientific research papers and reports. 6. Collaborate effectively in group tasks and discussions, contributing to the collective understanding of statistical concepts and their applications. 7. Demonstrate a solid statistical foundation, paving the way for further studies in more advanced statistical techniques and methodologies.

Navarro, D. J. (2019). Learning Statistics with R: A tutorial for psychology students and other beginners. Adelaide, Australia: University of Adelaide Press. Available online: https://learningstatisticswithr.com/ Peck, R., Olsen, C., & Devore, J. L. (2011). Introduction to Statistics and Data Analysis. Boston: Cengage Learning.                                                       Weiss, N. A. (2015). Introductory Statistics. Boston: Pearson

Moore, D. S., Notz, W. I., & Flinger, M. A. (2018). The Basic Practice of Statistics. New York: W. H. Freeman and Company.

    Triola, M. F. (2017). Elementary Statistics. Boston: Pearson.

    De Veaux, R. D., Velleman, P. F., & Bock, D. E. (2016). Intro Stats. Boston: Pearson.

    Diez, D. M., Barr, C. D., & Çetinkaya-Rundel, M. (2014). OpenIntro Statistics. CreateSpace Independent Publishing Platform.

    Peck, R., Olsen, C., & Devore, J. L. (2011). Introduction to Statistics and Data Analysis. Boston: Cengage Learning.

    Johnson, R. A., & Kuby, P. (2016). Just the Essentials of Elementary Statistics. Boston: Cengage Learning.

    Agresti, A., & Franklin, C. (2013). Statistics: The Art and Science of Learning from Data. Boston: Pearson.

Attendance is crucial for success in this course, and students are expected to attend at least 70% of lectures and seminar sessions

Class activities: Two-semester exams and a final oral exam.

The final course grade is based on 100 points earned through the student’s continuous involvement in-class activities:

Fair (2) – 50 to 64 points

Good (3) – 65 to 79 points

Very good (4) – 80 to 89 points

Excellent (5) – 90 to 100 points

Earning credits:

Class activities contribute to 70% of the grade:

Exam 1 – maximum 35 points

Exam 2 – maximum 35 points

The final (oral) exam contributes to 30% of the grade:

Final exam – maximum of 30 points