EC122: Statistical Techniques A

Subham Kailthya
Module Leader

12/15 CATS - Department of Economics

Summer Module

Spring Module

Principal Aims

This module allows the students to become familiar with the basic concepts of statistics, including graphical analysis and simple calculations conducted on the data. It is intended to provide the students with basic data analysis skills as well as the foundations, necessary for the second year econometrics module.

Principal Learning Outcomes

12 CATS

:...acquire the tools of quantitative methods necessary to study core and optional first and second year modules in economics for the single honours course in Economics.

:...develop further their techniques of statistical methods and statistical modelling;

:...generate an awareness and analysis of data and of data handling.

15 CATS

To acquire the tools of quantitative methods necessary to study core and optional first and second year modules in economics.

To develop further their techniques of statistical methods and statistical modelling;

To generate an awareness and analysis of data and of data handling.

Syllabus

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.

Context

Core Module: V1L8 - Year 1, V7ML - Year 1, LM1D (LLD2) - Year 1
Optional Core Module: L1CA - Year 1
Optional Module: LM1D (LLD2) - Year 1, V7ML - Year 1, LV13 - Year 1
Pre or Co-requisites: At least a grade A in GCSE Mathematics, or equivalent.
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

Assessment Method: 12 CATS - Coursework (30%) + Online Examination (70%) 15 CATS - Coursework (40%) + 1.5-hour examination (Summer) (60%)
Coursework Details: 12 CATS: Online Examination (70%) , Set of 6 problem sets (6%) , Test 1 (12%) , Test 2 (12%)
15 CATS: 1.5-hour examination (Summer) (60%) , 1200 word Statistical Project (10%) , 6 x problem sets (6%) , Test 1 (12%) , Test 2 (12%)
Exam Timing: Summer

Exam Rubric

12 CATS - Time Allowed: 1.5 Hours, plus 15 minutes reading time.

Read all instructions carefully- and read through the entire paper at least once before you start entering your answers.

There are TWO sections in this paper. Answer ALL TEN questions in Section A using the Excel spreadsheet (40 marks total) and answer ALL FOUR questions in Section B inside this document (60 marks total).

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

You should not submit answers to more than the required number of questions. If you do, we will mark the questions in the order that they appear, up to the required number of questions in each section.

15 CATS - Time Allowed: 1.5 Hours, plus 15 minutes reading time.

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.