# Introduction

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.

# Learning Outcomes

The course contents of the subject serve following objectives:

• Use graphical and numerical methods to calculate and illustrate descriptive statistics.
• Use the basic concepts of probability and Bayes Theorem.
• Identify the statistical concepts in questions about economic models.
• Use Excel to make basic statistical calculations and critically evaluate the basis for these calculations.
• Manipulate the probability models that are most widely used in economics, and apply them correctly and carry out the appropriate statistical analysis. Identify the appropriate regression model to apply to an economics dataset.
• Identify common problems which may affect regression analyses.

1. Amir, D.A. 1995. Statistics, Concepts and Applications, Richard D.Irwan Inc, USA.
2. Boweman, B. and R.T.O’connel. 1997. Applied Statistics Improving Business Process, Richard D. Irwan Inc, USA.
3. Chaudhry, S.M. & Mamal, S. (1998) Introduction to statistical theory parts I & II, Ilmi Kutab Khana, Urdue Bazar, Lahore.
4. Walpole, R.E. (1982). Introduction to Statistics (4th Ed). Mac. Millan Publishing Co. New York.
5. Sprent P. 1989. Applied Nonparametric Statistical Methods, Chapman and Hall, London.

# Assesment Criteria

• Mid Term Exam: 30 Marks
• Final Term Exam: 50  Marks
• Sessional: 30 Marks
• Project: 50%
• Presention: 30%
• Class Participation: 20%