Skip to main content Skip to navigation

EC122: Statistical Techniques A

  • Piotr Jelonek

    Module Leader
12/15 CATS - Department of Economics
Spring Module

Principal Aims

12 CATS - To provide an introduction to statistical ideas in economic and social studies, probability theory and techniques of statistical inference. The module provides a foundation in statistics necessary for core and optional modules in economics for PPE and EPAIS degree courses. It does not satisfy the requirement for EC226 Econometrics 1. The module forms part of the first year core cluster EC120 Quantitative Techniques, which is made up of one module in Mathematical Techniques (A (EC121) or B (EC123)), one module in Statistical Techniques (A (EC122) or B (EC124)) as well as Computing and Data Analysis (EC125).
15 CATS - To provide the requisite quantitative background for a thorough and rigorous study of economic analysis, econometric methods and applied economics subjects, commensurate with joint honours courses with Economics.

Principal Learning Outcomes

By the end of the module the student should be able to demonstrate an awareness of statistical ideas and a foundation in statistics.


Descriptive Statistics; Measures of location, dispersion, and asymmetry. Measurement of inequality, the Lorenz curve and the Gini coefficient; Probability theory; The concept of probability, events, The rules of probability. Independent events. Random variables and probability distributions. Discrete random variables: Bernoulli, binomial, Poisson. Expectations and variance. Continuous random variables: uniform, Gaussian (‘Normal’) distributions; The distinction between risk and uncertainty. Bivariate probability distributions; joint, marginal and conditional probability distributions; covariance and correlation. Statistical Inference; Sampling and sampling distributions for means and proportions. Applications of the t, ch-square and F distributions; Point estimation and confidence intervals; Hypothesis testing. Type I and Type II errors. Significance level and power of a test; Two variable correlation and regression. Testing for dependence between two variables.


Optional Core Module
LM1D (LLD2) - Year 1, V7ML - Year 1, L1L8 - Year 1, R3L4 - Year 1, R4L1 - Year 1, R2L4 - Year 1, R1L4 - Year 1
Pre or Co-requisites
At least a grade A in GCSE Mathematics, or equivalent.
Pre-requisite for
12 CATS - This module is restricted to LM1D/LLD2, V7ML and Joint Economics and Modern Language students and L1L8 students on Route B.
15 CATS - This module is restricted to L1L8 students
Part-year Availability for Visiting Students
12 CATS - Available in the Spring term only (2 x test - 9.6 CATS) and in the Spring and Summer terms together (2 x tests and 1 x 1.5 hour exam – 12 CATS)
15 CATS - Not available on a part-year basis


Assessment Method
12 CATS - Coursework (25%) + 1.5 hour exam (75%)
15 CATS - Coursework (30%) + 1.5 hour exam (70%)
Coursework Details
12 CATS - Two 50 min tests (worth 12.5% each)
15 CATS - Two 50 min tests (10% each), 1200 word statistical project (10%)
Exam Timing

Exam Rubric

Time Allowed: 1.5 Hours, plus 15 minutes reading time during which notes may be made (on the question paper) BUT NO ANSWERS MAY BE BEGUN.

Answer ALL SEVEN questions. Answer questions 1-4 in one booklet and questions 5-7 in a separate booklet

Approved pocket calculators are allowed. Statistical tables and a formula sheet are provided.

Read carefully the instructions on the answer book provided and make sure that the particulars required are entered on each answer book.

Previous exam papers can be found in the University’s past papers archive. Please note that previous exam papers may not have operated under the same exam rubric or assessment weightings as those for the current academic year. The content of past papers may also be different.

Reading Lists