Data Analytics II

Course Directors: Håkan Lyckeborg, Rickard Sandberg

Content

**DA** In this course the students will learn the basics of Econometrics (for cross-sectional data) and get an introduction to Machine Learning (ML). These learnings will form the basis for methods and applications in the subsequent course Data Analytics III. This course also includes further essential mathematical methods, bulding on the mathematical methods taught in the Data Analytics I course, that are used in economic and financial analysis and other areas. The importance of data science to businesses is discussed, with a primary focus on the opportunities and challenges that business school students face when encountering this field. Applications and practical implications are addressed, and the students will get further inspiration by a guest lecture (by people from the Swedish industry).

This course covers important econometric concepts such as: random sample, central limit theorem, estimation, inference (hypothesis testing), regression models, causality, randomized experiments, as well as the ML concepts: supervised learning (prediction and classification), unsupervised learning (clustering).

In this course the program Python is used to facilitate the learning of Econometrics and ML. The students will use different Python-packages for the analysis of regression models, causality, randomized experiments, prediction, classification, clustering, etc., and the students will also learn how data and results can be visualized.

Math This course also introduces some mathematics: integration, topics in financial mathematics, and matrices.

Format & Structure

Describe the teaching method and course structure – written assignments, cases, group work, etc.Lectures, seminars, tutoring, guest lecture(s) and exercises, both with and without the use of statistical software (Python). Explanations and applications relevant to business and economics. An individual case study (projektarbete) on real-world data using Python.

Course Administrator: Anna.Burell@hhs.se

After successfully completing this course students should be able to:
- solve problems that require knowledge about standard concepts of Econometrics and ML
- recognize the importance of data science to businesses
- perform basic Econometric and ML analysis on real-world data sets
- solve problems in Financial Mathematics and understand the usefulness and power of matrices

It is highly recommended that the prerequisite high school mathematics is well reviewed before the start of the course. Knowledge corresponding to the course Data Analytics I is required.

Minor adjustments may be made before registration

(After course start, no updated info here in Portal)

Newbold, Paul, Carlson, W.L. & Thorne, B., Statistics for Business and Economics, 10th Global edition 2022. Chapters 6 – 14. ISBN 9781292436845. (It is possible to use 9th ed., 2020. Chapters 6 – 14. ISBN 9781292315034.)

Python Data Science Handbook by Jake VanderPlas. This book is available as a free PDF download.

Sydsaeter, Knut, Peter Hammond, Arne Strom, Andrés Carvajal. Essential Mathematics for Economic Analysis, 6h ed., 2021. Chaptrs 10 – 11, 12 – 13. (Studied according to reading instructions handed out.) ISBN 9781292359281. (It is possoble to use the 5th ed., 2016. Chapters 9 – 10, 15 – 16. (Studied according to reading instructions handed out.) ISBN 9781292074610.

These textbooks are also core literature in Data Analytics I.

Supplementary material on Causality and Randomized Experiments.

(After course start, no updated info here in Portal)

Math: The fourth intended learning outcome will be assessed through a separate written exam ("Dugga"), Math. For the dugga the highest grade granted is Pass.

DA: The intended learning outcomes will be assessed through a written exam at the end of the course. The study case ("projekarbete") is mandatory to solve and will be assessed through a written report.

The final grade for the course is based on hand in assignments, 10 %, and the written exam, 90 %.

Find the course schedule in TimeEdit

Have you been granted educational support because of a documented disability? If so, please contact the course director as soon as possible so that adequate accommodations can be made.

Contact specialneeds@hhs.se if you have questions about being granted educational support or need a copy of your educational support certificate.

For more information, visit the Specific Educational Needs page on the Student Hub (login required).