Learning from Quantitative Data

This information is for the 2016/17 session.

Teacher responsible

Mr Revi Panidha


This course is compulsory on the BSc in Management. This course is available as an outside option to students on other programmes where regulations permit and to General Course students.


Quantitative Methods (Mathematics) (MA107) or equivalent and Quantitative Methods (Statistics) (ST107) or equivalent

Course content

Simple and Multiple Regression; Hypothesis Testing; Mechanics and Limitations of OLS; Causality; Natural, Field and Laboratory Experiments. Panel Data and Fixed Effect Models. Instrumental Variables Regression. The main aim of this course is to provide a thorough understanding of the quantitative techniques which guide evidence-based managerial decision-making. It seeks to develop a framework in which students can examine whether the predictions of managerial, social or economic theory are supported by empirical evidence. Particular emphasis is made on (a) illustrating the many ways in which evidence is abused in the academic or managerial debate, and (b) trying to establish causality in the relationship between variables. The approach is both formal, as the course makes extensive use of econometric theorems and techniques, and solidly grounded in intuition, as it provides numerous examples of tests of real-life relations. Many of these examples will be illustrated using the STATA software package, and the students will be expected to learn the basics of data manipulation and regression running. A solid base of introductory statistics and probability (equivalent to that provided by ST107) and introductory algebra and calculus (equivalent to that provided by MA107) will be expected.


20 hours of lectures and 10 hours of classes in the MT. 20 hours of lectures and 10 hours of classes in the LT. 2 hours of lectures and 1 hour of classes in the ST.

Students on this course will have a reading week in Week 6, in line with departmental policy.

Formative coursework

There will be 1 formative assessments each term. The first problem set of each term will be marked but will not count towards your grade.  

Indicative reading

The textbook for the course is: James H. Stock and Mark W. Watson, Introduction to Econometrics, Second Edition, Pearson, 2007.

Two other very useful (complementary) books are: Christopher Dougherty, Introduction to Econometrics, Third Edition, Oxford University Press, 2007; Jeffrey M. Wooldridge, Introductory Econometrics - A Modern Approach, Third Edition, South-Western, 2006.


Exam (80%, duration: 3 hours) in the main exam period.
In class assessment (20%) in the MT and LT.

There will be 4 in-class summative assessments each term. The best 3 out of 4 of these will count towards your final grade.These in-class assessments will take place during lectures.

Key facts

Department: Management

Total students 2015/16: 80

Average class size 2015/16: 12

Capped 2015/16: No

Lecture capture used 2015/16: Yes (MT & LT)

Value: One Unit

Guidelines for interpreting course guide information

PDAM skills

  • Problem solving
  • Application of information skills
  • Application of numeracy skills
  • Specialist skills

Course survey results

(2013/14 - 2015/16 combined)

1 = "best" score, 5 = "worst" score

The scores below are average responses.

Response rate: 100%



Reading list (Q2.1)


Materials (Q2.3)


Course satisfied (Q2.4)


Lectures (Q2.5)


Integration (Q2.6)


Contact (Q2.7)


Feedback (Q2.8)


Recommend (Q2.9)