BAD 2323 – Business Statistics Final Exam Study Guide • Margin of error – The value added to and subtracted from a point estimate in order to develop

Margin of error

The value added to and subtracted from a point estimate to develop an interval estimate of the population parameter.

t distribution

Used for computing an interval estimate for the difference between the means of two populations, not restricted to small samples.

Standard normal distribution

A probability distribution with a mean of 0 and a standard deviation of 1.

Parameters

Numerical characteristics of a population.

Hypothesis

An assumption made about the value of a population parameter.

ANOVA procedure

A statistical approach for determining whether or not the means of three or more populations are equal.

Factor

The independent variable of interest in an ANOVA procedure.

Treatments

Different levels of a factor in an ANOVA.

Chi-square distribution

The sampling distribution used when making inferences about a single population’s variance.

Goodness of fit test

A statistical test conducted to determine whether to reject or not reject a hypothesized probability distribution for a population.

Sampling distribution

A probability distribution of all possible values of a sample statistic.

Null hypothesis

The tentative assumption about the population parameter in hypothesis testing.

Power curve

Provides the probability of correctly rejecting the null hypothesis.

Mean square

The sum of squares divided by its corresponding degrees of freedom.

Confidence level

Describes the ability of an interval estimate to contain the value of the population parameter.

Sampling error

The difference between the sample mean and the population mean.

Replication

The number of times each experimental condition is observed in a factorial design.

Marascuilo procedure

Used to test for a significant difference between pairs of population proportions.

Interactions

The response produced when treatments of one factor interact with treatments of another in influencing the response variable.