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# Solutions for Chapter 2.9: Independent Random Vaariables ## Full solutions for Probability and Statistics with Reliability, Queuing, and Computer Science Applications | 2nd Edition

ISBN: 9781119285427 Solutions for Chapter 2.9: Independent Random Vaariables

Solutions for Chapter 2.9
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##### ISBN: 9781119285427

Since 6 problems in chapter 2.9: Independent Random Vaariables have been answered, more than 3399 students have viewed full step-by-step solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Probability and Statistics with Reliability, Queuing, and Computer Science Applications , edition: 2. Probability and Statistics with Reliability, Queuing, and Computer Science Applications was written by and is associated to the ISBN: 9781119285427. Chapter 2.9: Independent Random Vaariables includes 6 full step-by-step solutions.

Key Statistics Terms and definitions covered in this textbook
• 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

• 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.

• Bimodal distribution.

A distribution with two modes

• Bivariate distribution

The joint probability distribution of two random variables.

• Box plot (or box and whisker plot)

A graphical display of data in which the box contains the middle 50% of the data (the interquartile range) with the median dividing it, and the whiskers extend to the smallest and largest values (or some deined lower and upper limits).

• 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.

• 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.

• 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.

• Cumulative distribution function

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

• 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.

• Discrete random variable

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

• Distribution function

Another name for a cumulative distribution function.

• Empirical model

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

• Extra sum of squares method

A method used in regression analysis to conduct a hypothesis test for the additional contribution of one or more variables to a model.

• Fractional factorial experiment

A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.

• Generator

Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.

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