FAI3002 Quantitative Methods with Real Estate Applications 7.5 credits
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Content and learning outcomes
The course is divided into the following main parts:
1. Regression analysis using cross sectional data.
In this part, we study how to establish and quantify relationships between variables, mainly on the real estate market. To do this we will first discuss the technique of regression analysis, both for simple regression analysis and for multiple regression analysis.
2. Regression analysis using time series data.
In this part, we study the central issues regarding regression analysis when applied to data over longer periods, i.e., a time series. We look at both time series analysis and residual analysis.
Intended learning outcomes
After taking this course you should be able to use, understand och interpret quantitative methods, e.g., regression analysis, to examine the real estate market, analyse trends, conduct forecasting and construct index series.
Literature and preparations
Admission to postgraduate studies.
Announced when the course starts.
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
- RAP1 - Report, 7.5 credits, grading scale: P, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
Opportunity to complete the requirements via supplementary examination
Opportunity to raise an approved grade via renewed examination
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.
Further information about the course can be found on the Course web at the link below. Information on the Course web will later be moved to this site.Course web FAI3002