***COURSE NOW FULL***
Prerequisites: No previous knowledge of statistics will be assumed, but the use of formulae and the ability to perform basic algebraic manipulations will be necessary. Some knowledge of basic calculus, although not necessary, would be an advantage.
Dr Miltiadis Mavrakakis
Dr Erik Baurdoux
Course Structure: The content of the course will be presented by formal lectures supported by classes. The lectures will explain the concepts and methods of statistics, and will demonstrate these with practical examples. Full lecture notes will be given for each lecture and sets of exercises will be distributed. These are a vital part of the course and their solutions will be discussed in the classes; full worked solutions will also be distributed. Visual learning material will also be available for each chapter, allowing students to watch recorded videos of lectures and problem-solving for all topics covered in the course.
Course Objectives: This is an introductory course on statistics, with examples to demonstrate its applications in business and economics. There will be a strong emphasis on the concepts and application of probability theory, random variables, distributions, sampling theory, statistical inference, correlation and linear regression.
Statistical inference techniques such as estimation and significance testing are important in the fitting and interpretation of econometric models. Correlation and regression analysis are essential tools for measuring relationships between variables and for prediction.
This course should be of value to those intending to study any course involving economic modelling and econometrics.
There will be no need to rely on a particular textbook, as full notes will be provided. There are several good textbooks at the right level for this course, such as:
P. Newbold, Statistics for Business and Economics (6th edition or later), Prentice Hall (2007-).
R.J. Larsen and M.L. Marx, An Introduction to Mathematical Statistics and Its Applications (3rd edition or later), Prentice Hall (2001-).
Lectures: 36 hours Classes: 12 hours
Assessment: Two written examinations