Course Syllabus
Draft Syllabus: Foundations of Data Analysis |
| Semester & Location: |
Fall 2025 - DIS Copenhagen |
| Type & Credits: |
Elective Course - 3 credits |
| Major Disciplines: | Statistics |
| Faculty Members: |
TBA |
| Program Director: |
Natalia Landázuri Sáenz, PhD |
| Program Contact: | |
| Time & Place: |
TBA |
Course Description
This course aims to provide students with an understanding of the fundamentals of data analysis, with focus on descriptive and inferential statistics, and with a strong emphasis on quantitative reasoning. In this course, students will assess real-world data and will learn to apply statistical processes to real-life situations.
Classes will include lectures, a weekly lab to put into practice statistical analysis of data, as well as project work and exams.
Course elements
- Statistical analysis methods
- Statistical language
- Evaluation of statistical results
Topics
- Sampling and data
- Center and spread of data
- Normal distribution model
- Sampling distributions
- Descriptive statistics
- Hypothesis testing with one sample
- Dependent and independent t-test
- ANOVA
- Chi-square, goodness of fit, and test of independence
- Regression analysis, linear regression and correlation
Learning Objectives
Upon successfully completing the course, the student will be able to:
- Form their own research questions and successfully create a research study to address the questions posed
- Select and utilize appropriate statistical analysis methods to answer specific research questions
- Comprehensively convey results from data analysis, using clear and suitable statistical language
- Evaluate results from data analysis utilizing critical thinking skills, identify potential limitations and implications, and reflect on parameters and results associated with data analysis from an ethical perspective
Field Studies
There will be two course-integrated field studies to learn how to apply the foundational concepts of data analysis in academic research and industry work.
Field studies may include:
Visit to the Danish Technical University (DTU)
Visit to Københavns Kommune to learn about Statistikbank
Guest Lecturers
Guest lecturers may be invited to talk about topics of particular interest to students.
Faculty
TBA
Readings and tools
Excel will be used during labs for statistical analysis. It is required of all students to have Excel on their computer.
The course will not follow a particular textbook. Specific book chapters and online resources will be available on Canvas when addressing particular topics. They may include:
Introductory Statistics, openstax (https://openstax.org/details/books/introductory-statistics-2e/)
Expectations of the Students
- You should participate actively during lectures, discussions, group work, and exercises.
- Laptops may be used for note‐taking, fact‐checking, or assignments in the classroom, but only when indicated by the instructor. At all other times, laptops and electronic devices should be put away during class meetings.
- Readings must be done prior to the class session.
- In addition to completing all assignments and exams, you need to be present, arrive on time, and actively participate in all classes and field studies to receive full credit. Your final grade will be affected, adversely, by unexcused absences and lack of participation. Your participation grade will be reduced by 10 points (over 100) for every unexcused absence. Remember to be in class on time!
- Classroom etiquette includes being respectful of other opinions, listening to others and entering a dialogue in a constructive manner.
- You are expected to ask relevant questions in regards to the material covered.
- Excuses for any emergency absences must be given beforehand. It is the responsibility of the student to make up any missed coursework.
DIS Accommodations Statement
The student learning experience in this class is important. If a student has approved academic accommodations with DIS, please ensure a DIS accommodations letter is shared with the faculty within two weeks from the start of classes. Students are encouraged to share additional ways their learning can be supported. If you have any further questions about your academic accommodations, contact Academic Support acadsupp@dis.dk.
Evaluation
Students will be evaluated based on their performance on the course assignments. This includes labs, assigned homework, exams, attendance, and a semester project.
Inappropriate and/or unprofessional behavior (e.g., sleeping during presentations, being rude towards our hosts during field studies) results in a score of 0 for participation for the entire semester.
Grading
When assigning the final grades, your efforts will weigh as follows:
|
Semester Project |
20% |
|
Exams |
20% |
|
Homework |
20% |
|
Labs |
30% |
|
Active participation (including attendance) |
10% |
Active participation: Includes attendance, preparation for lectures and other sessions, active participation in learning activities, class discussions, group work and problem solving. It also includes active participation during field studies and presentation of reflections on how they are related and relevant within the context of the course.
Homework and labs: Homework and instructions for labs will be posted on Canvas. Students may be allowed to work in groups to complete their work (specific information is posted on Canvas). Late submissions will be deducted by 10 points for each day the homework is late.
Mid-term exam: Mid-way through the semester, you will take an exam that covers all topics covered thus far in the course.
Exam: At the end of the semester, you will take an exam that covers all topics from the course.
Semester Project: Students will work in groups to apply concepts covered during the course, compile and analyze datasets, and clearly state conclusions and reflections.
Academic Regulations
Please make sure to read the Academic Regulations on the DIS website. There you will find regulations on:
DIS - Study Abroad in Scandinavia - www.DISabroad.org