ST201      Half Unit
Statistical Models and Data Analysis

This information is for the 2016/17 session.

Teacher responsible

Dr Nicholas Cron (COL2.04)


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

Also available to students who have studied statistics and mathematics to the level of MA107/ST107 Quantitative Methods. Not to be taken in conjunction with ST203 Statistics for Management Sciences (Full unit).

Course content

A second course in statistics with an emphasis on problems of practical importance and statistical analysis using computers. Principles of modelling: data preparation, mathematical and statistical models, linear and non-linear models. Simple linear regression. Multiple regression: assumptions, transformations, diagnostics, model selection. Logistic regression: odds ratios and likelihood. Introduction to time series: smoothing, seasonal adjustment, autocorrelation.


20 hours of lectures and 16 hours of computer workshops in the LT. 4 hours of lectures in the ST.

Students will be given their assessed project to start on in week 6 which is due in at the end of LT.

Formative coursework

Moodle quizzes and a quantitative research project.

Indicative reading

Heij et al (2008), Econometric Methods with Applications in Business and Economics;

Baddeley & Barrowclough (2009), Running Regressions: A Practical Guide to Quantitative Research in Economics, Finance and Development Studies;

Diaz et al (2014), OpenIntro Statistics.


Exam (80%, duration: 2 hours) in the main exam period.
Coursework (20%) in the LT.

Student performance results

(2013/14 - 2015/16 combined)

Classification % of students
First 59
2:1 25
2:2 13.5
Third 1.9
Fail 0.6

Key facts

Department: Statistics

Total students 2015/16: 58

Average class size 2015/16: 20

Capped 2015/16: No

Lecture capture used 2015/16: Yes (LT)

Value: Half Unit

Guidelines for interpreting course guide information

PDAM skills

  • Self-management
  • Problem solving
  • Application of information skills
  • Application of numeracy skills
  • Specialist skills