Statistical Methods for Economics

Statistical Methods for Economics (SME)

1. Introduction and Overview 

The distinction between populations and samples and between population parameters and sample statistics; the use of measures of location and variation to describe and summarize data; population moments and their sample counterparts.

2. Elementary Probability Theory 

Sample spaces and events; probability axioms and properties; counting techniques; conditional probability and Bayes’ rule; independence.

3. Random Variables and Probability Distributions 

Defining random variables; probability distributions; expected values of random variables and of functions of random variables; properties of commonly used discrete and continuous distributions (uniform, binomial, normal, poisson and exponential random variables).

4. Random Sampling and Jointly Distributed Random Variables 

Density and distribution functions for jointly distributed random variables; computing expected values; covariance and correlation coefficients.

5. Sampling 

Principal steps in a sample survey; methods of sampling; the role of sampling theory; properties of random samples.

6. Point and Interval Estimation 

Estimation of population parameters using methods of moments and maximum likelihood procedures; properties of estimators; confidence intervals for population parameters.

Textbook:
1. Jay L. Devore, Probability and Statistics for Engineers
Plus Notes and Tutes