POLS 160
Statistics for Social Sciences
Instructor: Dr. Öğr. Üyesi SÜLEYMAN CENGİZCİ
Course Objectives
The course's main goal is to provide a thorough and self-contained description of classical or mainstream statistical theory and its applications (in the sense that the necessary probability theory is included).
Prerequisites / Corequisites
NA
Course Books / Materials / Recommended Resources
Camm et al., Business Analytics: Descriptive, Predictive, Prescriptive, 4th edition,Cengage, 2020.S. C. Albright, Business Analytics: Data Analysis and Decision Making, 7th edition,Cengage, 2020.
Academic Integrity and Artificial Intelligence
Violations of scholastic honesty include, but are not limited to cheating, plagiarizing, fabricating information or citations, facilitating acts of dishonesty by others, having unauthorized possession of examinations, submitting work of another person or work previously used without informing the instructor, or tampering with the academic work of other students. Any form of scholastic dishonesty is a serious academic violation and will result in disciplinary action. Regarding the use of generative artificial intelligence (GenAI) tools in this course, the provisions of the 'Ethical Guide on the Use of Generative Artificial Intelligence in Scientific Research and Publication Activities of Higher Education Institutions (2024)' published by the Council of Higher Education (YÖK) shall apply.
View in course information package → Download course PDF Back to list