Lesson 1

Random Experiment

An experiment that can be repeated numerous times under the same conditions. Its result must be independent of one another.

Outcome

The result of a random experiment.

Sample Space

The set of possible outcomes of a random experiment.

Random Variable

A function that associates a numerical value to every outcome of a random experiment.

Discrete Random Variable

Random variable with a finite number of possible values or an infinite number of values that can be counted.

Continuous Random Variable

Random variable that can assume an infinite number of values that can take decimal or fractional value.

Probability Distribution of a Discrete Random Variable

Is a list, a table, a graph, or a formula of probabilities associated with each of its possible values.

Mean

The expected value of X.

Standard Normal Distribution

If the mean is 0 and the standard deviation is 1, then the normal distribution is a ___.

Bell-Shaped

Shape of distribution curve.

Population

Group where members have something in common, that is, the total set of observations that can be made.

Sample

A smaller group or subset of the population in question.

Parameter

Describes an entire population.

Statistics

Describes only the sample.

Simple Random Sampling

The simplest way of getting random sample where each member of the population has an equal chance of being chosen as the sample.

Stratified Random Sampling

This involves selecting a simple random sample from each of a given number of subpopulations. Each subpopulation is called a stratum.

Cluster Sampling

The population is first divided into separate groups called clusters. Then, a simple random sample of clusters from the available clusters in the population is selected.

Systematic Random Sampling

This involves the random selection of one of the first k elements in an ordered population, and then the systematic selection of every kth element thereafter.

Multistage Sampling

Two or more probability techniques are combined. It can be described as sampling within the sample.

Sampling Distribution

This is a probability distribution of a statistic obtained from all possible samples of a particular size from a population.

Central Limit Theorem

The sampling distribution of the sample mean of any population approaches a normal distribution as the sample size increases, regardless of the distribution of the population.