# 2019/2020  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)
• Statistics and quantitative methods
Teaching methods
• Face-to-face teaching
Last updated on 30/03/2020

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
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