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Get Full Access to Statistics - Textbook Survival Guide
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# Solutions for Chapter 15: Distribution-Free Procedures

## Full solutions for Probability and Statistics for Engineering and the Sciences (with Student Suite Online) | 7th Edition

ISBN: 9780495382171

Solutions for Chapter 15: Distribution-Free Procedures

Solutions for Chapter 15
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##### ISBN: 9780495382171

Probability and Statistics for Engineering and the Sciences (with Student Suite Online) was written by and is associated to the ISBN: 9780495382171. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 15: Distribution-Free Procedures includes 36 full step-by-step solutions. This textbook survival guide was created for the textbook: Probability and Statistics for Engineering and the Sciences (with Student Suite Online), edition: 7. Since 36 problems in chapter 15: Distribution-Free Procedures have been answered, more than 20142 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.

• 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).

• Acceptance region

In hypothesis testing, a region in the sample space of the test statistic such that if the test statistic falls within it, the null hypothesis cannot be rejected. This terminology is used because rejection of H0 is always a strong conclusion and acceptance of H0 is generally a weak conclusion

• Alternative hypothesis

In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test

• Arithmetic mean

The arithmetic mean of a set of numbers x1 , x2 ,…, xn is their sum divided by the number of observations, or ( / )1 1 n xi t n ? = . The arithmetic mean is usually denoted by x , and is often called the average

• Average

See Arithmetic mean.

• Causal variable

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

• Completely randomized design (or experiment)

A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.

• Continuous random variable.

A random variable with an interval (either inite or ininite) of real numbers for its range.

• Contour plot

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

• Cumulative sum control chart (CUSUM)

A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t

• Defect concentration diagram

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

• Discrete uniform random variable

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

• Error mean square

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

• Error of estimation

The difference between an estimated value and the true value.

• Event

A subset of a sample space.

• False alarm

A signal from a control chart when no assignable causes are present

• Fraction defective

In statistical quality control, that portion of a number of units or the output of a process that is defective.

• Frequency distribution

An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on

• Hat matrix.

In multiple regression, the matrix H XXX X = ( ) ? ? -1 . This a projection matrix that maps the vector of observed response values into a vector of itted values by yˆ = = X X X X y Hy ( ) ? ? ?1 .

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