- Chapter 1: Probability Theory
- Chapter 10: Discrete Data Analysis
- Chapter 11: The Analysis of Variance
- Chapter 12: Simple Linear Regression and Correlation
- Chapter 13: Multiple Linear Regression and Nonlinear Regression
- Chapter 14: Multifactor Experimental Design and Analysis
- Chapter 15: Nonparametric Statistical Analysis
- Chapter 16: Quality Control Methods
- Chapter 17: Reliability Analysis and Life Testing
- Chapter 2: Random Variables
- Chapter 3: Discrete Probability Distributions
- Chapter 4: Continuous Probability Distributions
- Chapter 5: The Normal Distribution
- Chapter 6: Descriptive Statistics
- Chapter 7: Statistical Estimation and Sampling Distributions
- Chapter 8: Inferences on a Population Mean
- Chapter 9: Comparing Two Population Means
Probability and Statistics for Engineers and Scientists 4th Edition - Solutions by Chapter
Full solutions for Probability and Statistics for Engineers and Scientists | 4th Edition
Probability and Statistics for Engineers and Scientists | 4th Edition - Solutions by ChapterGet Full Solutions
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
Asymptotic relative eficiency (ARE)
Used to compare hypothesis tests. The ARE of one test relative to another is the limiting ratio of the sample sizes necessary to obtain identical error probabilities for the two procedures.
See Arithmetic mean.
Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.
A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.
Components of variance
The individual components of the total variance that are attributable to speciic sources. This usually refers to the individual variance components arising from a random or mixed model analysis of variance.
The probability of an event given that the random experiment produces an outcome in another event.
Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.
A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria
A square matrix that contains the correlations among a set of random variables, say, XX X 1 2 k , ,…, . The main diagonal elements of the matrix are unity and the off-diagonal elements rij are the correlations between Xi and Xj .
Another name for factors that are arranged in a factorial experiment.
Deming’s 14 points.
A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality
The response variable in regression or a designed experiment.
An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment
Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.
A subset of a sample space.
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
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.
Fraction defective control chart
See P chart
The geometric mean of a set of n positive data values is the nth root of the product of the data values; that is, g x i n i n = ( ) = / w 1 1 .
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