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2020/2021  BA-BSEMO1005U  Method ll. Statistics and quantitative methods

English Title
Method ll. Statistics and quantitative methods

Course information

Language English
Course ECTS 7.5 ECTS
Type Mandatory
Level Bachelor
Duration One Quarter
Start time of the course Third Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for BSc in Service Management
Course coordinator
  • H.C. Kongsted - Department of Strategy and Innovation (SI)
Main academic disciplines
  • Statistics and quantitative methods
Teaching methods
  • Blended learning
Last updated on 22-06-2020

Relevant links

Learning objectives
Upon completion of the course, the students should be able to:
  • Explain different kinds of population characteristics (types of variables), their measurement from a sample, and sampling biases.
  • Explain and discuss the concept of probability and the concept of inference, and relate to measures of test statistics, critical value, confidence interval and p-value.
  • Explain and perform appropriate tests of hypotheses about means and proportions
  • Explain and perform tests of hypotheses about the association between two categorical variables.
  • Explain the concept of correlation between numerical variables, and compute a correlation coefficient
  • Explain the logic of regression analysis and the difference between correlation and regression analyses. Formulate and discuss adequate regression models for explaining different phenomena.
  • Perform linear regression, including multivariate regression and regression with categorical (dummy) variables as explanatory variables. Interpret regression coefficients and related measures (t-tests, F-tests, standard errors, p-values etc.) and the determination coefficient (R2), and investigate residuals.
Course prerequisites
English language skills equal to B2 level (CEFR) and math skills equal to Danish level B are recommended
Examination
Method II. Statistics and quantitative methods:
Exam ECTS 7,5
Examination form Written sit-in exam on CBS' computers
Individual or group exam Individual exam
Assignment type Written assignment
Duration 4 hours
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Spring
Aids Limited aids, see the list below:
The student is allowed to bring
  • USB key for uploading of notes, books and compendiums in a non-executable format (no applications, application fragments, IT tools etc.)
  • Any calculator
  • In Paper format: Books (including translation dictionaries), compendiums and notes
The student will have access to
  • Access to Canvas
  • Access to the personal drive (S-drive) on CBS´ network
  • Advanced IT application package
Make-up exam/re-exam
Same examination form as the ordinary exam
If the number of registered candidates for the make-up examination/re-take examination warrants that it may most appropriately be held as an oral examination, the programme office will inform the students that the make-up examination/re-take examination will be held as an oral examination instead.
Description of the exam procedure

Feedback after exam:
• Suggested answers for exam questions
• Office hours (one week) for individual queries
 

Course content, structure and pedagogical approach

The course addresses established statistical methods for representing and analyzing quantitative data, primarily survey data. The focus will be on selecting and applying the methods that are appropriate for a given type of data. Students will learn how phenomena can be measured and analyzed statistically, how to report  the results of their analysis, and what kind of conclusions statistical research can lead to. 

The main modules composing the course are:

• Probability

• Confidence intervals and hypothesis testing

• Tests of hypotheses about means and proportions

• Tests of association between categorical variables

• Correlation analysis
• Regression analysis

 

Students will learn how to perform statistical analyses in Microsoft Excel.

Description of the teaching methods
Lectures (introduce statistical theory, example, cases); workshops (train how to select, apply and report the appropriate method for analyzing a particular data set); homework exercises (in preparation for lectures and workshops).
Feedback during the teaching period
Feedback during term:
• Office hours
• Follow-up on workshop assignment during following week’s lectures
Student workload
Classes 30 hours
Reading and homework exercises 130 hours
Attending workshops 10 hours
Preparation for written exam 55 hours
Expected literature
  • Alan Agresti, Christine Franklin, Bernhard Klingenberg: ‘Statistics. The Art and Science of learning from Data’, 4th Edition. Pearson Education International. Chapters 1-4, and 6-13. Exclusive of sections 4.3, 6.3, 8.5, 9.6, 11.4-11.5, 12.5, 13.6). 582 pages.

Please note, minor changes may occur. The teacher will upload the final reading list to CBS Canvas two weeks before the course starts.

Last updated on 22-06-2020