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
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