EC275 STATISTICS FOR ECONOMICS SEMESTER 2 2012-2013

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EC275 STATISTICS FOR ECONOMICS
SEMESTER 2
2012-2013
Lecturer:
Dr Paddy Gillespie
[email protected]
Room 213, First Floor, Cairnes Building
Office Hours:
Thursdays 2-4pm.
Tutor:
Danny Norton
[email protected]
Dr Joe Higgins Room, First Floor, Cairnes Building
Lecture Times:
Monday 5-6pm
MRA201 MR1 Theatre, Martin Ryan Annexe Building
Wednesday 10-11am
Darcy-Thompson Theatre, Concourse Building
Tutorials:
Tuesdays 10-11am, 11-12pm or 12-1pm (Week 2)
Friary Suite, Cairnes Building.
Course Description:
This is an introductory course in statistics designed to provide an overview of the techniques
used to collect, present, analyse and utilise numerical data to make inferences and reach
decisions in the face of uncertainty in economics, business, and other social and physical
sciences. Statistics is subdivided into descriptive and inferential. Descriptive statistics is
concerned with summarising and describing a body of data. Inferential statistics is the process
of reaching generalisations about the whole (i.e. the population) by examining a portion (i.e. the
sample). Topics include populations and samples; the presentation and interpretation of data;
measures of central tendency and variability; basic probability; discrete and continuous
probability distributions; and estimation and hypothesis testing.
Textbook:
Lind/Marchal/Wathen - Basic Statistics for Business and Economics, 8th Ed, McGraw-Hill
Copies are available in the library and in the NUI Galway campus bookshop.
Lectures and Tutorials:
Students are expected to attend two lecture hours and one tutorial hour per week. Lectures
consist of a mixture of multimedia presentations, practical examples of real world data using
statistical packages, and problem sets. Tutorials are designed to assist students in revising
course materials with particular emphasis placed on solving problem sets and practical
applications. All course materials will be posted on BLACKBOARD prior to class.
Assessment:
Course evaluation is entirely (100%) on the basis of continuous assessment. The course is
divided into three sections and will be graded via 3 take-home assignments (worth 40% in
total) and 3 in-class examinations (worth 60% in total). Please see below for further details
on the dates of assignments and examinations and for the course grading system.
Topic Guide, Reading and (Preliminary) Timetable:
Topic
Descriptive
Statistics
Wks
4
Reading
Chapter 1: What is Statistics?
Chapter 2: Frequency
Distributions and Graphic
Presentation
Week Commencing
January 7th : 2 lecture hours
January 14th: 2 lecture hours
January 21rd: 2 lecture hours
January 27th: 1 lecture hour; 1 hour
Exam
Chapter 3: Numerical Measures
Assessment/%
Inferential
Statistics 1
4
Chapter 4: Exploring Data
Take-home assignment = 14%
In-class exam = 20%
Chapter 5: A Survey of Probability
Concepts
Chapter 6: Discrete Probability
Distributions
Available: Jan 21st /Due: Jan28st
Wednesday January 30th
February 4th: 2 lecture hours
February 11th: 2 lecture hours
February 18th: 2 lecture hours
February 25th: 1 lecture hour; 1
hour Exam
Chapter 7: Continuous Probability
Distributions
Assessment/%
Inferential
Statistics 2
4
Chapter 8a: Sampling Methods
and the Central Limit Theorem
Take-home assignment = 13%
In-class exam = 20%
Chapter 8b: Sampling Methods
and the Central Limit Theorem
Chapter 9: Estimation and
Confidence Intervals
Available: Feb18h/Due: Feb 25th
Wednesday February 27nd
March 4th: 2 lecture hours
March 11th: 2 lecture hours
March 18th: 1 lecture hour
March 25th: 1 lecture hour; 1 hour
Exam
Chapter 10: One-Sample Tests of
Hypothesis
Assessment/%
Chapter 11: Two-Sample Tests of
Hypothesis
Take-home assignment = 13%
In-class exam = 20%
Available: Mar 18th/ Due: Mar25th
Wednesday March 27th
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