This preview shows pages 1–2. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.View Full Document
Unformatted text preview: 1 CHAPTER 5 SAMPLING DISTRIBUTIONS FOR MEANS In section 1.3, we used normal probability tables to find probabilities for random variables from normally distributed populations. Population Distribution The population distribution of a variable is the distribution of its values for all members of the population. The population distribution is also the probability distribution of the variable when we choose one individual from the population at random. The Distribution of a Statistic A statistic from a random sample or randomized experiment is a random variable. The probability distribution of the statistic is its sampling distribution. If our random variable follows a normal distribution as in chapter 1.3, we can use the normal tables to calculate probabilities. In reality, however, our random variable seldom follows a normal distribution. However, due to the central limit theorem, we are able to use the normal distribution in calculating probabilities for statistics that come from non-normal populations. Central Limit Theorem Draw an SRS of size n from any population with mean and finite standard deviation . When n is large, the sampling distribution of the sample mean x is approximately normal: x is approximately ( , ) N n In other words, when your sample size ( n ) is large enough, the distribution of X...
View Full Document
This note was uploaded on 02/28/2012 for the course STAT 301 taught by Professor Staff during the Spring '08 term at Purdue University-West Lafayette.
- Spring '08