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Solutions for Chapter 8.5: Interval Estimation

Full solutions for Introduction to Probability and Statistics 1 | 14th Edition

ISBN: 9781133103752

Solutions for Chapter 8.5: Interval Estimation

Solutions for Chapter 8.5
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ISBN: 9781133103752

This expansive textbook survival guide covers the following chapters and their solutions. Since 17 problems in chapter 8.5: Interval Estimation have been answered, more than 9685 students have viewed full step-by-step solutions from this chapter. Chapter 8.5: Interval Estimation includes 17 full step-by-step solutions. This textbook survival guide was created for the textbook: Introduction to Probability and Statistics 1, edition: 14. Introduction to Probability and Statistics 1 was written by and is associated to the ISBN: 9781133103752.

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

A fractional factorial experiment with k factors tested in a 2 ? p fraction with all factors tested at only two levels (settings) each

• 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

• Attribute

A qualitative characteristic of an item or unit, usually arising in quality control. For example, classifying production units as defective or nondefective results in attributes data.

• Bernoulli trials

Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

• Causal variable

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

• Contingency table.

A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria

• Continuous random variable.

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

• Control limits

See Control chart.

• 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 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

• Curvilinear regression

An expression sometimes used for nonlinear regression models or polynomial regression models.

• Degrees of freedom.

The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.

• Dependent variable

The response variable in regression or a designed experiment.

• Discrete uniform random variable

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

• Erlang random variable

A continuous random variable that is the sum of a ixed number of independent, exponential random variables.

• Forward selection

A method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.

• 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.

• Frequency distribution

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

• Goodness of fit

In general, the agreement of a set of observed values and a set of theoretical values that depend on some hypothesis. The term is often used in itting a theoretical distribution to a set of observations.

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