Difference between revisions of "Statistics"

From ECLR
Jump to: navigation, search
(The Basics)
(The Basics)
Line 35: Line 35:
 
|-
 
|-
 
| [[Regression|Correlation & Regression]]
 
| [[Regression|Correlation & Regression]]
| Exercises
+
| [[Regression_Examples|Exercises]]
 
| Correlation only
 
| Correlation only
 
| Yes
 
| Yes

Revision as of 10:10, 9 August 2013

This page is currently being build and should be completed for the start of Academic Year 2013/14.

The purpose of these pages is to give prospective and current postgraduate students in Economics at The University of Manchester an opportunity to understand what Statistics knowledge they are expected to have and, of course, a source of revision information. The material presented here is largely based on material written by our colleagues Len Gill, Denise Osborn and Chris Orme at The University of Manchester.

This page is explicitly designed with MSc Economics (and/or Econometrics) and MA Economics students at The University of Manchester in mind. Below you will be able to identify which topic is expected knowledge for the MSc/MA.

The Basics

Topic MA Economics MSc Economics
Preliminaries and Notation Yes Yes
Data types Yes Yes
Graphical Representation Yes Yes
Descriptive Statistics Yes Yes
Correlation & Regression Exercises Correlation only Yes

Probability

Topic MA Economics MSc Economics
Introduction to Probability Yes Yes
Conditional Probability Yes Yes
Discrete Random Variables Yes Yes
Normal Distribution Yes Yes
Moments and Expectations Yes Yes


Statistical Inference

Example Data Sets

Throughout these pages a few example datasets will be used.

Description Organisation Data File Source
Data used to calculate a quality of Life Index OECD (collecting data from various sources) BetterLifeIndex.xls [1]
Exchange Rate USD/UKP Board of Governors of the Federal reserve System USDUKP.xlsx [2]
UK Gross Domestic Product Office of national Statistics UK_GDP_INF.xlsx [3]
Passengers on the Titanic Titanic.xlsx [4]
CO2 and GDP Gapminder.com GDP_CO2.xlsx [5]