KUGO 2005 - Introduction to Statistical Reasoning and Quantitative Methods

Intermediate group:

This course focuses on advanced statistical techniques and their practical applications to real-world problems. Its primary objective is to equip students with a comprehensive understanding of various estimation tools, with a particular emphasis on regression analysis. The course addresses how to select appropriate estimators based on the data, research question, or analytical objectives, how to assess the robustness of the results, and how to present findings in a clear and compelling manner.

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Beginner group:

This course is intended for those with little or no past training in quantitative methods. The course is an intensive introduction to some of the principles and methods of statistical analysis in social research. Topics covered in Introduction to Statistics include descriptive statistics, basic ideas of inference and estimation, contingency tables and linear regression models. Students will be introduced to the computer programs Excel, Stata, and R.

Textbook: - Alan Agresti (2018) Statistical Methods for the Social Sciences (Fifth Ed.). Pearson.

Assignments and Assessment

Intermediate group:

• Mid-Term Paper 30%

Objective: Apply foundational concepts covered in the first half of the course.

Details:

• Students will work individually on a dataset provided during lab sessions.
• Exercises will include:
• Descriptive statistics and visualizations,
• Simple regression analysis,
• Brief interpretation of results.
• Deliverable: A written report (3–4 pages, double-spaced) in PDF format.
• Final Project 50%

Objective: Synthesize concepts from the course and apply them to a practical question.

Details:

• The project will be completed in groups and will involve:
• Data cleaning and exploratory visualizations,
• Regression analysis suitable for the dataset,
• Interpretation of key findings.
• Deliverables:
• A 10-minute group presentation (20% of the final grade),
• A concise written report (5–6 pages, double-spaced) (30% of the final grade).
• Lab Participation 20%

Objective: Engage actively in hands-on learning during lab sessions.

Details:

• Students are expected to:
• Complete in-class exercises related to course topics,
• Collaborate effectively during group activities.
• Regular attendance and participation are required.

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Beginner group:

Class Participation 25%

Regular attendance and active participation are expected. Classroom participation is an essential part of this class and a great opportunity to practice interpreting results and running own analyses in the computer lab. Everyone is expected to contribute to the discussion to the best of their ability.

Mid-term Exam 30%

The mid-term exam will be a one-hour in-class exam where students are expected to show their ability to calculate and interpret basic descriptive statistics.

Final Exam 45%

The final exam comprises a two-hour in-class exam where students are expected to show their ability to interpret presented results based on regression analysis. A scientific calculator won’t be required to answer the exam questions, but students can bring one to the exam. Students are not allowed to use their phones.