# 2013/2014  BA-HAS_MIII  Methods III – Statistics and quantitative methods (for students enrolled in 2012 or earlier)

 English Title Methods III – Statistics and quantitative methods (for students enrolled in 2012 or earlier)

# Course information

Language English
Exam ECTS 7.5 ECTS
Type Mandatory
Level Bachelor
Duration One Quarter
Course period First Quarter
Time Table Please see course schedule at e-Campus
Study board
Study Board for BSc in Service Management
Course coordinator
• Per Vejrup-Hansen - Department of Innovation and Organizational Economics (INO)
• Statistics and mathematics
Last updated on 08-08-2013
Learning objectives
Through this course the students should be able to:
• Explain different kinds of measurement of characteristics (types of variables), and sampling biases.
• Illustrate, calculate, and interpret descriptive statistics (mean, median, variance, standard deviation) on numerical variables.
• Explain and discuss the concept of probability, and relate to measures of critical val-ue, confidence interval and p-value. Understand the concept of inference.
• Based on these concepts and measures, perform appropriate tests about a mean and about the difference between means (for example average incomes by two groups)
• Perform tests for proportions of values of categorical variables (fx. shares of votes in an election or preferences for various products), and about the association between two categorical variables (fx. gender and preferences).
• Explain and illustrate the concept of correlation between numerical variables, and compute a correlation coefficient (for example between household income and spending on a specific product).
• Explain the logic of regression analysis and explain the difference between correlation and regression analyses. Formulate and discuss adequate regression models for explaining phenomena.
• Perform linear and non-linear regression analyses, and further multivariate regression. Interpret regression coefficients (through standard errors, p-values etc.) and the determination coefficient R2, and investigate residuals.
• Include categorical (dummy) variables as explanatory variables in regression analysis.
Course prerequisites
English language skills equal to B2 level (CEFR) and math skills equal to Danish level B are recommended.
Examination
 Methods III – Statistics and quantitative methods: Examination form Written sit-in exam Individual or group exam Individual Exam guidelines: • The written exam takes place on CBS computers • Graphs can be written by hand • Students have access to their personal files (S-drive on CBS network) • Students do NOT have access to Internet, LEARN, and other services from CBS (except their personal S-drive on CBS network) • Students are not allowed to bring personal electronic devices to the exam, except a non-programmable calculator. Assignment type Written assignment Duration 4 hours Grading scale 7-step scale Examiner(s) Internal examiner and second internal examiner Exam period Autumn Term Aids allowed to bring to the exam Limited aids, see the list below and the exam plan/guidelines for further information: Additional allowed aidsAllowed calculatorsAllowed dictionariesBooks and compendia brought by the examineeNotes brought by the examinee 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.
Course content and structure

The course address established statistical methods for representing and analyzing quantitativedata, primarily survey data. The focus is on application of methods, not on statistical theory.
Students will learn how phenomena are measured statistically and what kind of conclusions statistical research can lead to.
Also, students will learn how to perform these analyses. The statistical software is Microsoft Excel which allows for basic analyses and understanding, and Excel is common software readily available. Main modules composing the course are:

• Descriptive Statistics
• Probability
• Hypothesis tests about means and proportions

• Test about the association between categorical variables

• Correlation Analysis
• Regression Analysis (the most extensive topic)

Teaching methods
Lectures, workshops, and homework exercises.