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# Solutions for Chapter 3.11: Nonlinear Models

## Full solutions for Advanced Engineering Mathematics | 5th Edition

ISBN: 9781449691721

Solutions for Chapter 3.11: Nonlinear Models

Solutions for Chapter 3.11
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##### ISBN: 9781449691721

This expansive textbook survival guide covers the following chapters and their solutions. Advanced Engineering Mathematics was written by and is associated to the ISBN: 9781449691721. This textbook survival guide was created for the textbook: Advanced Engineering Mathematics , edition: 5. Chapter 3.11: Nonlinear Models includes 25 full step-by-step solutions. Since 25 problems in chapter 3.11: Nonlinear Models have been answered, more than 37547 students have viewed full step-by-step solutions from this chapter.

Key Statistics Terms and definitions covered in this textbook
• 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

• Binomial random variable

A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.

• Bivariate distribution

The joint probability distribution of two random variables.

• Combination.

A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.

• Conditional probability mass function

The probability mass function of the conditional probability distribution of a discrete random variable.

• Cook’s distance

In regression, Cook’s distance is a measure of the inluence of each individual observation on the estimates of the regression model parameters. It expresses the distance that the vector of model parameter estimates with the ith observation removed lies from the vector of model parameter estimates based on all observations. Large values of Cook’s distance indicate that the observation is inluential.

• 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 .

• Correlation

In the most general usage, a measure of the interdependence among data. The concept may include more than two variables. The term is most commonly used in a narrow sense to express the relationship between quantitative variables or ranks.

• 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 .

• Critical region

In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.

• Critical value(s)

The value of a statistic corresponding to a stated signiicance level as determined from the sampling distribution. For example, if PZ z PZ ( )( .) . ? =? = 0 025 . 1 96 0 025, then z0 025 . = 1 9. 6 is the critical value of z at the 0.025 level of signiicance. Crossed factors. Another name for factors that are arranged in a factorial experiment.

• Cumulative distribution function

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

• Discrete random variable

A random variable with a inite (or countably ininite) range.

• Distribution function

Another name for a cumulative distribution function.

• Error of estimation

The difference between an estimated value and the true value.

• Estimate (or point estimate)

The numerical value of a point estimator.

• Estimator (or point estimator)

A procedure for producing an estimate of a parameter of interest. An estimator is usually a function of only sample data values, and when these data values are available, it results in an estimate of the parameter of interest.

• Exponential random variable

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

• Fisher’s least signiicant difference (LSD) method

A series of pair-wise hypothesis tests of treatment means in an experiment to determine which means differ.

• Fraction defective control chart

See P chart

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