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# Solutions for Chapter 5.4: 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 5.4

Solutions for Chapter 5.4
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##### ISBN: 9780073534985

This textbook survival guide was created for the textbook: Elementary Statistics: A Step By Step Approach , edition: 9. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 5.4 includes 14 full step-by-step solutions. Elementary Statistics: A Step By Step Approach was written by and is associated to the ISBN: 9780073534985. Since 14 problems in chapter 5.4 have been answered, more than 169125 students have viewed full step-by-step solutions from this chapter.

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

A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

• Analysis of variance (ANOVA)

A method of decomposing the total variability in a set of observations, as measured by the sum of the squares of these observations from their average, into component sums of squares that are associated with speciic deined sources of variation

• Backward elimination

A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

• Causal variable

When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable

• Chance cause

The portion of the variability in a set of observations that is due to only random forces and which cannot be traced to speciic sources, such as operators, materials, or equipment. Also called a common cause.

• Comparative experiment

An experiment in which the treatments (experimental conditions) that are to be studied are included in the experiment. The data from the experiment are used to evaluate the treatments.

• Conditional mean

The mean of the conditional probability distribution of a random variable.

• Conditional probability

The probability of an event given that the random experiment produces an outcome in another event.

• Contour plot

A two-dimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

• Counting techniques

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

• Covariance

A measure of association between two random variables obtained as the expected value of the product of the two random variables around their means; that is, Cov(X Y, ) [( )( )] =? ? E X Y ? ? X Y .

• Crossed factors

Another name for factors that are arranged in a factorial experiment.

• Cumulative normal distribution function

The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.

• Defect concentration diagram

A quality tool that graphically shows the location of defects on a part or in a process.

• Distribution function

Another name for a cumulative distribution function.

• Error mean square

The error sum of squares divided by its number of degrees of freedom.

• Estimate (or point estimate)

The numerical value of a point estimator.

• Expected value

The expected value of a random variable X is its long-term average or mean value. In the continuous case, the expected value of X is E X xf x dx ( ) = ?? ( ) ? ? where f ( ) x is the density function of the random variable X.

• Factorial experiment

A type of experimental design in which every level of one factor is tested in combination with every level of another factor. In general, in a factorial experiment, all possible combinations of factor levels are tested.

• Generating function

A function that is used to determine properties of the probability distribution of a random variable. See Moment-generating function

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