ECON 2P91 Lecture Notes - Lecture 3: Sampling Distribution, Random Variable, Null Hypothesis

• School: Brock University
• Department: Economics
• Course: ECON 2P91
• Professor: Tomson Ogwang

Document Summary

An estimator is a function of sample data to be drawn randomly from a population: is a random variable because of the randomness in selecting the sample, an estimator should be unbiased, consistent, and efficient. An estimate is the numerical value of the estimator when it is actually computed using data from a specific sample: is a nonrandom variable. The importance of random sampling: nonrandom sampling can result in being biased. A null hypothesis is the hypothesis to be tested. The null hypothesis is denoted (cid:2868) and thus is (cid:2868):e(y)= ,0. The most general alternative hypothese is that e(cid:523)y(cid:524) ,0. This is called a or greater than ,0. The two sided alternative is written as (cid:2869):e(cid:523)y(cid:524) ,0 sample of data to decide whether to accept the null hypothesis (cid:2868) or to reject it in favor of the alternative hypotheses (cid:2869).