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2020/2021  KAN-CIHCO2007U  Managerial Statistics for Innovation

English Title
Managerial Statistics for Innovation

Course information
Language English
Course ECTS 7.5 ECTS
Type Mandatory offered as elective
Level Full Degree Master
Duration One Quarter
Start time of the course First Quarter
Timetable Course schedule will be posted at calendar.cbs.dk
Max. participants 60
Study board
Study Board for MSc in Business Administration and Innovation in Health Care
Course coordinator
  • Francesco Di Lorenzo - Department of Strategy and Innovation (SI)
Main academic disciplines
  • Statistics and quantitative methods
Teaching methods
  • Blended learning
Last updated on 15-06-2020

Relevant links
Learning objectives
The objective is to introduce sensibly basics of descriptive and inferential statistics and build both a theoretical foundation and a practical knowledge about how to implement statistics in real analysis-based situations.
In this course attendants will learn about foundations of statistics, in particular: descriptive statistics (i.e. summary statistics), hypothesis testing (T-Test, Proportional Test, differences in groups’ distributions, etc.), goodness of fit (simple linear regression), multiple regression analysis and other more sophisticated estimators. Emphasis will be placed on interpretations of the statistics and applicability. Thus, attendants will apply statistical concepts to real data and touch typical data analyst challenges and ways out.
To be awarded the highest mark (12), the student, with no or just a few insignificant shortcomings, must fulfill the following learning objectives:
  • Understand the theoretical foundations of descriptive statistics
  • Understand the theoretical foundations of inferential statistics
  • Apply in practice descriptive statistics using real data
  • Apply in practice descriptive statistics using real data
Course prerequisites
No strict prerequisites.It would be ideal to have some familiarity with basic statistics.

This is a mandatory course for the MSc in Business Administration and Innovation in Health Care.

To sign up send a 1-page motivational letter and a grade transcript to ily.stu@cbs.dk before the registration deadline for elective courses. You may find the registration deadlines on my.cbs.dk ( https:/​/​studentcbs.sharepoint.com/​graduate/​pages/​registration-for-electives.aspx )

Please also remember to sign up through the online registration.
Examination
Managerial Statistics for Innovation:
Exam ECTS 7,5
Examination form Home assignment - written product
Individual or group exam Individual exam
Size of written product Max. 15 pages
Assignment type Report
Duration Written product to be submitted on specified date and time.
Grading scale 7-point grading scale
Examiner(s) One internal examiner
Exam period Winter
Make-up exam/re-exam
Same examination form as the ordinary exam
If a student did not pass the regular exam, he/she must make a new revised assignment (confer advice from the examiner) and hand it in on a new deadline specified by the secretariat.
If a student did not hand in the assignment due to illness, he/she will be able to hand it in on a new deadline. If for any other reason the student did not hand in the assignment, a new assignment will be given the student to hand in on a new deadline (confer advice from the examiner).
Description of the exam procedure

The exam will imply the following activities:
1.    Create a dataset
2.    Define one of few main research questions to be addressed within the scope of the database
3.    Apply the appropriate statistical techniques learned during the course to address the questions proposed at point #2.
4.    Provide statistical and economical considerations on the results of the analysis.

 

Skill developed: simulation of real business analytics-based on decision making, development of delivery-mindset, analytical skills, writing.
Course content, structure and pedagogical approach

Ideally the course will cover the basics of statistics in order provide the attendants with a solid basis on both descriptive and inferential statistics. Despite the introductory nature of the course, attendant will be expose to primary techniques of data analysis useful in real-life settings. Ideally, the first part of the course will be focused on Descriptive Statistics, which will be based on the following main questions:

 

  • How are data described? Which type of data are we in front of?
  • How do we define a variable?
  • What is a sample? What is the difference between sample and population?
  • What are the central tendency characteristics of variable?
  • How can we describe the dispersion of a variable? And its shape?

In the second part of the course, attendants will be introduce to foundations of Inferential statistics, thus dealing with the following questions:

 

  • What is the different between to group? How to assess it?
  • What is the relationship between two variables?
  • How do we create predictions?
  • What is an estimator?
  • How do we pick the correct estimator to predict our effect?
Description of the teaching methods
The course aims to be a balance between theory and practice. The theory will be delivered to make attendants aware about the necessary understanding of each statistics topic to have the eventual freedom to build their own analytical strategy. The practice will be delivered to train the attendants to the day-by-day challenges and mechanism in data analysis.
Ideally a lecture will have the following components:

• Delivery of the theory about a specific statistics topic.
• Acquisition of the analytical tool and individual practice in class guided by the
faculty
• Group exercise using real-life database

STATA (12.0 version or more recent) will be the software of reference for this course. Despite attendants will be instructed on the useful commands throughout the development of the course, attendants are still expected to familiarize themselves with basic ability in this software, such as uploading a file, save a DO and DTA file, and similar basic commands. MS Excel will be also used, in particular at the beginning of the seminar for the Descriptive Statistics section.
Feedback during the teaching period
I will meet at least one time with individual student during the course to feedback on their project.
Student workload
confrontation hours 30 hours
reading hours 111 hours
exam preparation 65 hours
Further Information
  • Highly interactive course in class
  • Most of the work is performed in class
  • Sessions are a mix of frontal teaching, class case discussion, small groups exercise.
  • Examination is about review main theoretical aspects and apply concepts discussed in class
  • Group work is relevant to the learning experience.
Expected literature

There is no a specific list of reference to use or requested or expected. Yet, suggested materials are (the most recent a version is, the better):

  • Berenson et al. Basic Statistics for Business, Pearson
  • Wooldridge, Introductory Econometrics: A modern approach, South-Western
  • Angrist and Pischke, Mostly Harmless Econometrics, Princeton University Press
Last updated on 15-06-2020