Solutions for Chapter 4.3: Elementary Statistics 12th Edition

The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.

An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest.

Unbiased estimator.

A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.

The simplest form of the central limit theorem states that the sum of n independently distributed random variables will tend to be normally distributed as n becomes large. It is a necessary and suficient condition that none of the variances of the individual random variables are large in comparison to their sum. There are more general forms of the central theorem that allow ininite variances and correlated random variables, and there is a multivariate version of the theorem.

See R 2 .

The probability mass function of the conditional probability distribution of a discrete random variable.

The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.

Another term for the conidence coeficient.

A continuous random variable with range of a inite interval and a constant probability density function.

A method to derive the probability density function of the sum of two independent random variables from an integral (or sum) of probability density (or mass) functions.

In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.

For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.

A probability distribution for a discrete random variable

A discrete random variable with a inite range and constant probability mass function.

A continuous random variable that is the sum of a ixed number of independent, exponential random variables.

A procedure for producing an estimate of a parameter of interest. An estimator is usually a function of only sample data values, and when these data values are available, it results in an estimate of the parameter of interest.

A subset of a sample space.

The distribution of the random variable deined as the ratio of two independent chi-square random variables, each divided by its number of degrees of freedom.

Another name for the normal distribution, based on the strong connection of Karl F. Gauss to the normal distribution; often used in physics and electrical engineering applications