# Solutions for Chapter 6.2: Elementary Statistics: A Step By Step Approach 9th Edition

## Full solutions for Elementary Statistics: A Step By Step Approach | 9th Edition

ISBN: 9780073534985

Solutions for Chapter 6.2

Solutions for Chapter 6.2
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##### ISBN: 9780073534985

Elementary Statistics: A Step By Step Approach was written by Sieva Kozinsky and is associated to the ISBN: 9780073534985. This expansive textbook survival guide covers the following chapters and their solutions. Since 36 problems in chapter 6.2 have been answered, more than 50770 students have viewed full step-by-step solutions from this chapter. Chapter 6.2 includes 36 full step-by-step solutions. This textbook survival guide was created for the textbook: Elementary Statistics: A Step By Step Approach , edition: 9th.

Key Statistics Terms and definitions covered in this textbook
• 2 k p - factorial experiment

A fractional factorial experiment with k factors tested in a 2 ? p fraction with all factors tested at only two levels (settings) each

• `-error (or `-risk)

In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

• a-error (or a-risk)

In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).

• Analytic study

A study in which a sample from a population is used to make inference to a future population. Stability needs to be assumed. See Enumerative study

• Asymptotic relative eficiency (ARE)

Used to compare hypothesis tests. The ARE of one test relative to another is the limiting ratio of the sample sizes necessary to obtain identical error probabilities for the two procedures.

• Axioms of probability

A set of rules that probabilities deined on a sample space must follow. See Probability

• Central tendency

The tendency of data to cluster around some value. Central tendency is usually expressed by a measure of location such as the mean, median, or mode.

• Conditional probability distribution

The distribution of a random variable given that the random experiment produces an outcome in an event. The given event might specify values for one or more other random variables

• Conidence level

Another term for the conidence coeficient.

• Continuous distribution

A probability distribution for a continuous random variable.

• Counting techniques

Formulas used to determine the number of elements in sample spaces and events.

• Cumulative distribution function

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

• Defects-per-unit control chart

See U chart

• Deming’s 14 points.

A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality

• Empirical model

A model to relate a response to one or more regressors or factors that is developed from data obtained from the system.

• Error propagation

An analysis of how the variance of the random variable that represents that output of a system depends on the variances of the inputs. A formula exists when the output is a linear function of the inputs and the formula is simpliied if the inputs are assumed to be independent.

• Estimate (or point estimate)

The numerical value of a point estimator.

• Experiment

A series of tests in which changes are made to the system under study

• Forward selection

A method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.

• Geometric random variable

A discrete random variable that is the number of Bernoulli trials until a success occurs.

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