Regression Analysis
Study Board of Market and Management Anthropology, Economics, Mathematics-Economics, Environmental and Resource Management
Teaching language: Danish or English depending on the teacher
EKA: B540009102
Censorship: Second examiner: None
Grading: 7-point grading scale
Offered in: Odense
Offered in: Autumn
Level: Bachelor
Course ID: B540009101
ECTS value: 10
Date of Approval: 19-04-2022
Duration: 1 semester
Course ID
Course Title
Teaching language
ECTS value
Responsible study board
Study Board of Market and Management Anthropology, Economics, Mathematics-Economics, Environmental and Resource Management
Date of Approval
Course Responsible
Offered in
Level
Offered in
Duration
Recommended prerequisites
Students enrolled in the course are expected to have passed the following courses or their equivalents: Mathematics (9105701 / B540006101) and Statistics (9116001 / B540023101),
Aim and purpose
The objective of the course is to give the student a thorough introduction to the multiple linear regression model and the R software environment, which are essential tools for empirical analysis in business and economics.
Content
The primary focus of the course will be the analysis of the multiple linear regression model, including specification, estimation, and testing of the model and its assumptions. The course deals mainly with the analysis of cross-sectional data, in which observations are assumed to be independent.
Students will be introduced to R, a programming language, and RStudio, a free and open-source integrated development environment (IDE) for R, which are specifically developed for statistical computing, data manipulation, graphical display, and regression-based analysis. In addition, the students will be given a basic introduction to linear algebra and matrix notation.
Students will be given the opportunity to work on practical applications of all the theoretical methods and concepts introduced in the course. An important part of the course is the exercise sets, in which students will perform empirical analyses in R using both actual and simulated data. The student teacher will review the solutions to the exercises in the tutorial sessions.
Description of outcome - Knowledge
Demonstrate knowledge about the course’s areas of focus, enabling the student to:
- Formulate the multiple linear regression model and its underlying assumptions in matrix form
- Describe statistical properties of estimated parameters in the multiple linear regression model
- Identify a properly specified multiple linear regression model
- Describe the consequences of multicollinearity, omitted variables, functional form misspecification, and heteroskedasticity in multiple regression models
- Acquire a toolbox of R packages and functions required to perform regression-based analysis
Description of outcome - Skills
Demonstrate skills, such that the student is able to:
- Import data into R to conduct preliminary descriptive analysis and regression-based analysis
- Estimate and interpret the parameters of multiple linear regressions in R
- Perform hypothesis tests concerning the parameters of multiple regression models
- Implement functions in R to evaluate the adequacy of the estimated regression models and perform tests for omitted variables, functional form misspecification, and neglected heteroskedasticity
- Conduct valid estimation strategies in regression models with heteroskedastic error terms
Description of outcome - Competences
Demonstrate competences, such that the student is able to:
- Correctly apply the appropriate commands in R to perform empirical analyses using the multiple linear regression model in the context of different applications in the fields of business and economics
- Critically assess the validity of empirical studies based on regression analysis in business and economics
Literature
Course textbook: There is one required textbook for the course.
- Econometric Methods with Applications in Business and Economics (2004), Christiaan Heij, Paul de Boer, Philip Hans Franses, Teun Kloek, and Herman K. van Dijk. Oxford University Press.
Econometrics books: There are a number of recommended textbooks for this course which may complement the required textbook. These are generally written at a less technical level and provide more intuition than Heij et al.
- Wooldridge, Jeffrey M. (2015). Introductory Econometrics – A Modern Approach. Cengage Learning. 6th Edition.
- Introduction to Econometrics, 4th ed. by James H. Stock and Mark W. Watson.
Supplementary materials: Teaching notes and online texts.
Teaching Method
Workload
Schedule of classes:
4 (2x2) lectures for 15 weeks.
2 tutorials for 14 weeks (starting the week after the start of semester).
Workload:
For the average student, the teaching activities are distributed according to the following estimate:
Class lectures - 60 hours
Tutorials - 28 hours
Preparation for class lectures - 70 hours
Preparation for tutorials - 72 hours
Preparation for exam - 40 hours
Total 270 hours
This corresponds to an average weekly workload of 13 hours during the semester, including the exam.
Examination regulations
Written exam
Name
Written exam
Timing
Exam: January
Reexam: February
Tests
Written exam with own PC
Name
Written exam with own PC
Form of examination
Written examination on premises
Censorship
Second examiner: None
Grading
7-point grading scale
Identification
Student Identification Card - Exam number
Language
English
Duration
4 hours
Length
No limitations.
Examination aids
All exam aids allowed. However, it is not allowed to communicate with anybody.
Assignment handover
The assignment is handed over in Digital Exam.
Assignment handin
The assignment is handed over in Digital Exam.
ECTS value
10
Additional information
EKA
B540009102
External comment
Examination in this course is not allowed if the student has passed the course Social Science Methods (9054602).
Courses offered
| Offer period | Offer type | Profile | Education | Semester |
|---|---|---|---|---|
| Fall 2022 | Mandatory | Fra 1. september 2023 optages der ikke længere studerende på denne linje - Bacheloruddannelsen i Økonomi - Erhvervsøkonomisk linje, Odense, gældende fra 1. september 2020 | BSc in Economics - 2022 | Bachelor of Science in Economics | Odense | |
| Fall 2022 | Mandatory | Fra 1. september 2023 optages der ikke længere studerende på denne linje - Bacheloruddannelsen i Økonomi - Samfundsøkonomisk linje, Odense, gældende fra 1. september 2020 | BSc in Economics - 2022 | Bachelor of Science in Economics | Odense | Fall 2022 | Exchange students |