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# Solutions for Chapter 10.8: Categorical Data and Nonparametric Methods

## Full solutions for Probability and Statistics | 4th Edition

ISBN: 9780321500465

Solutions for Chapter 10.8: Categorical Data and Nonparametric Methods

Solutions for Chapter 10.8
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##### ISBN: 9780321500465

Since 16 problems in chapter 10.8: Categorical Data and Nonparametric Methods have been answered, more than 8647 students have viewed full step-by-step solutions from this chapter. Probability and Statistics was written by and is associated to the ISBN: 9780321500465. Chapter 10.8: Categorical Data and Nonparametric Methods includes 16 full step-by-step solutions. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Probability and Statistics, edition: 4.

Key Statistics Terms and definitions covered in this textbook
• `-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).

• All possible (subsets) regressions

A method of variable selection in regression that examines all possible subsets of the candidate regressor variables. Eficient computer algorithms have been developed for implementing all possible regressions

• 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

• Assignable cause

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.

• Average

See Arithmetic mean.

• Biased estimator

Unbiased estimator.

• Bivariate normal distribution

The joint distribution of two normal random variables

• C chart

An attribute control chart that plots the total number of defects per unit in a subgroup. Similar to a defects-per-unit or U chart.

• Center line

A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.

• Conditional probability

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

• Conidence coeficient

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

• Control limits

See Control chart.

• Correction factor

A term used for the quantity ( / )( ) 1 1 2 n xi i n ? = that is subtracted from xi i n 2 ? =1 to give the corrected sum of squares deined as (/ ) ( ) 1 1 2 n xx i x i n ? = i ? . The correction factor can also be written as nx 2 .

• Decision interval

A parameter in a tabular CUSUM algorithm that is determined from a trade-off between false alarms and the detection of assignable causes.

• Deming

W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

• Designed experiment

An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

• Experiment

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

• Exponential random variable

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

• First-order model

A model that contains only irstorder terms. For example, the irst-order response surface model in two variables is y xx = + ?? ? ? 0 11 2 2 + + . A irst-order model is also called a main effects model

• Frequency distribution

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

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