# Statistics 1 - Description and Inference

Course
2023-2024

## Course description

This course is intended to introduce students to quantitative methods of data analysis in the social sciences. The course introduces students to basic statistics: how to summarize large amounts of information efficiently and how to draw basic inferences. As political scientists, we are interested in answering questions such as “What is the association between political systems and the involvement in international wars?”. To answer such questions we require 1) data and 2) methods and techniques to process and analyze such data. In this course, you will learn how to describe data, apply and interpret the results from simple statistical tests and effect measures, such as the t-test, ANOVA, chi-square test and association measures, and familiarize yourself with statistical software. A more detailed weakly program will be announced via Brightspace.

## Course objectives

Objective 1: Students can calculate and interpret a number of univariate data statistics (measures of central tendency and measures of dispersion) and confidence intervals.
Objective 2: Students can calculate and report, as well as critically evaluate others’ use and interpretation of, a number of bivariate statistical analyses.
Objective 3: Students have basic skills in using software for quantitative analysis.

## Mode of instruction

This course is taught through a combination of online weblectures, one weekly (in-person) Q&A lecture and one weekly seminar. The weblectures introduce students to statistical analysis and follow the course textbook. In seminars, students will familiarize themselves with the statistical software and apply the concepts and methods that were covered in the lecture. Students are required to prepare assignments and submit these via Brightspace.

## Literature and Software

Literature:

• Diez, D. M., Barr, C. D., & Çetinkaya-Rundel, M. (2019). OpenIntro statistics (Fourth edition). OpenIntro.
o The book is offered on the Pay-What-You-Want model, including a free version. More information can be found here: https://www.openintro.org/book/os/
o The Ebook version of OpenIntro is available here: https://leanpub.com/os

• Additional teaching materials (articles, videos, websites, and other tools) will be made available on Brightspace. If not stated otherwise, these materials can also be part of the exam.
Software:

• In this course you will learn how to use R and RStudio for effective data analysis. RStudio is an open-source tool that allows you to work in R more simply and more efficiently.

• R (version 4.2.1) and RStudio are pre-installed on all university computers.
This course uses Brightspace. Students are required to check the course page regularly for announcements, course materials and to submit assignments.

## Registration

See 'Practical Information'

## Assessment

• Participation: 10 %

• Assignments: 20 %

• Written final exam: 70 % (combination of closed questions and open questions)
More details on the assessment will be provided via Brightspace at the start of the course.
Attention: you need to enroll before the deadline via uSis to take the final written exam!
You are required to obtain at least a grade of 5.0 on the final written test to pass the course. If you obtain a final “fail” course mark you can only resit the final written exam. Smaller partial grades (participation and assignment grade) cannot be retaken.
The time and location of the post-exam review session will be announced via Brightspace no later than the publication of the grades.

## Timetable - subjects and exams

See 'MyTimetable'