 82.81: 81. For a normal population with known variance 2 , answer the fol...
 82.82: For a normal population with known variance 2 : (a) What value of i...
 82.83: 83. Consider the onesided confidence interval expressions, Equati...
 82.84: A confidence interval estimate is desired for the gain in a circuit...
 82.85: 85. Consider the gain estimation problem in Exercise 84. How larg...
 82.86: Following are two confidence interval estimates of the mean of the ...
 82.87: 87. n 100 random samples of water from a fresh water lake were tak...
 82.88: The breaking strength of yarn used in manufacturing drapery materia...
 82.89: 89. The yield of a chemical process is being studied. From previou...
 82.810: The diameter of holes for cable harness is known to have a normal d...
 82.811: 811. A manufacturer produces piston rings for an automobile engine...
 82.812: The life in hours of a 75watt light bulb is known to be normally d...
 82.813: 813. A civil engineer is analyzing the compressive strength of con...
 82.814: Suppose that in Exercise 812 we wanted to be 95% confident that th...
 82.815: 815. Suppose that in Exercise 812 we wanted the total width of th...
 82.816: Suppose that in Exercise 813 it is desired to estimate the compres...
 82.817: 817. By how much must the sample size n be increased if the length...
 82.818: If the sample size n is doubled, by how much is the length of the C...
Solutions for Chapter 82: CONFIDENCE INTERVAL ON THE MEAN OF A NORMAL DISTRIBUTION, VARIANCE KNOWN
Full solutions for Applied Statistics and Probability for Engineers  3rd Edition
ISBN: 9780471204541
Solutions for Chapter 82: CONFIDENCE INTERVAL ON THE MEAN OF A NORMAL DISTRIBUTION, VARIANCE KNOWN
Get Full SolutionsChapter 82: CONFIDENCE INTERVAL ON THE MEAN OF A NORMAL DISTRIBUTION, VARIANCE KNOWN includes 18 full stepbystep solutions. Since 18 problems in chapter 82: CONFIDENCE INTERVAL ON THE MEAN OF A NORMAL DISTRIBUTION, VARIANCE KNOWN have been answered, more than 22688 students have viewed full stepbystep 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: Applied Statistics and Probability for Engineers , edition: 3. Applied Statistics and Probability for Engineers was written by and is associated to the ISBN: 9780471204541.

`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).

Alias
In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

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.

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.

Bivariate normal distribution
The joint distribution of two normal random variables

Central tendency
The tendency of data to cluster around some value. Central tendency is usually expressed by a measure of location such as the mean, median, or mode.

Conditional variance.
The variance of the conditional probability distribution of a random variable.

Continuous uniform random variable
A continuous random variable with range of a inite interval and a constant probability density function.

Control limits
See Control chart.

Convolution
A method to derive the probability density function of the sum of two independent random variables from an integral (or sum) of probability density (or mass) functions.

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

Dependent variable
The response variable in regression or a designed experiment.

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.

Exhaustive
A property of a collection of events that indicates that their union equals the sample space.

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.

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.

Geometric random variable
A discrete random variable that is the number of Bernoulli trials until a success occurs.

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.