果冻传媒

Introduction

This module allows students to develop an understanding of fundamental and intermediate concepts of statistical analysis, such as regression analysis. Students will also develop the capacity to apply statistical techniques to real world problems/data sets using the statistical package STATA.

Principal Aims

The module aims to provide students with important skills which are of both academic and vocational value, being an essential part of the intellectual training of an economics and social scientist and also useful for a career.

Principal Learning Outcomes

Subject Knowledge and Understanding:...demonstrate understanding of random variables, associated distributions and moments; statistical estimation, estimator sampling distributions and population inference; causality and selection bias; experimental versus non-experimental data; simple linear regression (SLR) model, assumptions, interpretation and hypothesis testing; multiple linear regression (MLR) model, assumptions, interpretation and hypothesis testing; modelling non-linear relationships; dummy variables; interaction terms; the failure of MLR assumptions; tests and implications for hypothesis testing; problems of endogeneity; instrumental variables; short panel data methods; Stata.

Knowledge and understanding of:... (i) Economic Principles including analysis of economic decisions in microeconomics. (ii) An awareness of the empirical approach to economics and social science. (iii) Reviewing and extending fundamental statistical concepts, including causal analysis and (iv) Regression analysis, its extensions and applications.

Syllabus

Context

Core Module

L1L8 - Year 2

Optional Core Module

V7MR - Year 2, R3L4 - Year 2

Optional Module

V7ML - Year 3

Pre or Co-requisites

Any of

EC106-24 Introduction to Economics OR

EC107-30 Economics 1 OR

All of

EC139-15 Mathematical Techniques A and

EC122-15 Statistical Techniques A OR

All of

EC140-15 Mathematical Techniques B and

EC124-12 Statistical Techniques B OR

All of

IB122-15 Business Analytics

Summary:

Modules: EC106-24 or EC107-30 or (EC139-15 and EC122-12) or (EC140-15 and EC124-12)

Restrictions

May not be combined with modules EC226-30

Assessment

Assessment Method

Coursework (30%) + Centrally-timetabled examination (On-campus) (70%)

Coursework Details

Centrally-timetabled examination (On-campus) (70%) , Empirical Assignment (10%) , Test 1 (10%) , Test 2 (10%)

Exam Timing

Summer

Reading Lists