INTRODUCTION TO ECONOMETRICS II ECO 306 NOUN 18 1.1.1.0 Introduction
1.1.2.0
Objectives 1.1.3.0 Main Content
1.1.3.1 Random Variables and Sampling Theory
1.1.3.2 Expected values
of discrete random variable 1.1.3.3 Expected value rules
1.1.3.4 Sampling theory
1.1.3.4.1
Some terminology 1.1.3.4.2 Reasons for sampling
1.1.3.4.3 Types of sampling technique
1.1.3.4.4 Simple
Random Sampling technique 1.1.3.5 Estimation of Population Mean
1.1.4.0 Summary
1.1.5.0
Conclusion 1.1.6.0 Tutor-Marked Assignment
1.1.7.0 References/Further Reading
1.1.1.0 INTRODUCTION Random variable or stochastic variable is a variable whose possible values are numerical products of a chance occurrence. As a function, a random variable is required to be quantifiable, which rules out certain uncontrolled circumstances where the quantity which the random variable returns is considerably sensitive to small changes in the outcome. It is common that these outcomes depend on some physical variables that are not well understood. For example,
when you toss a coin, which outcome will be observed is not certain. The domain of a random variable is the set of possible outcomes. In the case of the coin, there are only two possible outcomes, namely heads or tails. The domain of the random variable leads us into the concept of sampling theory which is concerned with the theory involved in the selection of a subset of individuals from within a statistical population estimates the characteristics of the whole population.
