Statistics for Economics | ECON1007 | University of Southampton

Module overview

All economics students, on both single and joint honours programmes, take this course. It is optional for students outside of economics. The module is designed to prepare students for the econometrics modules taken in second and third year. It also complements the economics modules taken in by students in first and second year. It provides an introduction to the topic of statistics, with reference to economics examples. It then covers more advanced topics leading up to regression analysis.

The course content is as follows: describing data; probability; discrete random variables; continuous random variables; sampling; estimation; hypothesis testing; simple regression and multiple regression.

One of the pre-requisites for MATH2040, MATH3085, ECON1021, ECON2001, ECON2002, ECON2003, ECON2004, ECON2026 and ECON3016.

Aims and Objectives

Learning Outcomes

Transferable and Generic Skills

Having successfully completed this module you will be able to:

Use Excel to make basic statistical calculations and critically evaluate the basis for these calculations;

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

Identify common problems which may affect regression analyses
Use graphical and numerical methods to calculate and illustrate descriptive statistics
Manipulate the probability models that are most widely used in economics, and apply them correctly and carry out the appropriate statistical analysis
Identify the statistical concepts in questions about economic models

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

Identifying the appropriate regression model to apply to an economic dataset
The basic concepts of probability and Bayes Theorem

Syllabus

1. Describing data

2. Probability

3. Discrete Random Variables

4. Continuous Random Variables

5. Sampling

6. Estimation

7. Hypothesis Testing

8. Simple Regression

9. Multiple Regression

Learning and Teaching

Teaching and learning methods

The course is based on lectures and tutorials, and students may also use interactive online resources listed on Blackboard..

Study time
Type	Hours
Lecture	24
Seminar	8
Independent Study	118
Total study time	150

Resources & Reading list

General Resources

Excel software.

University of Southampton e books collection.

Internet Resources

for Apps.

Websites.

for Apps.

Textbooks

Statistics for Business and Economics. Pearson.

Assessment

Assessment strategy

The assessment in this module is by group coursework in form of two problem sets (10% of the final mark each) and an end of module examination (80%). This is the same for internal repeats. Referral and external repeat assessment are through 100% end of module examination.

Summative

This is how we’ll formally assess what you have learned in this module.

Breakdown
Method	Percentage contribution
Coursework	10%
Coursework	10%
Exam	80%

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Breakdown
Method	Percentage contribution
Exam	100%

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.

Breakdown
Method	Percentage contribution
Exam	100%

Repeat Information

Repeat type: Internal & External