- Chapter 1: Overview and Descriptive Statistics
- Chapter 10: The Analysis of Variance
- Chapter 11: Multifactor Analysis of Variance
- Chapter 12: Simple Linear Regression and Correlation
- Chapter 13: Nonlinear and Multiple Regression
- Chapter 14: Goodness-of-Fit Tests and Categorical Data Analysis
- Chapter 15: Distribution-Free Procedures
- Chapter 16: Quality Control Methods
- Chapter 2: Probability
- Chapter 3: Discrete Random Variables and Probability Distributions
- Chapter 4: Continuous Random Variables and Probability Distributions
- Chapter 5: Joint Probability Distributions and Random Samples
- Chapter 6: Point Estimation
- Chapter 7: Statistical Intervals Based on a Single Sample
- Chapter 8: Tests of Hypotheses Based on a Single Sample
- Chapter 9: Inferences Based on Two Samples
Probability and Statistics for Engineering and the Sciences 8th Edition - Solutions by Chapter
Full solutions for Probability and Statistics for Engineering and the Sciences | 8th Edition
Probability and Statistics for Engineering and the Sciences | 8th Edition - Solutions by ChapterGet Full Solutions
A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain
Bivariate normal distribution
The joint distribution of two normal random variables
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.
When a factorial experiment is run in blocks and the blocks are too small to contain a complete replicate of the experiment, one can run a fraction of the replicate in each block, but this results in losing information on some effects. These effects are linked with or confounded with the blocks. In general, when two factors are varied such that their individual effects cannot be determined separately, their effects are said to be confounded.
A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria
A probability distribution for a continuous random variable.
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 .
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.
A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).
Defects-per-unit control chart
See U chart
A matrix that provides the tests that are to be conducted in an experiment.
Discrete random variable
A random variable with a inite (or countably ininite) range.
Error of estimation
The difference between an estimated value and the true value.
The variance of an error term or component in a model.
A subset of a sample space.
A signal from a control chart when no assignable causes are present
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.
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.
Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.
Having trouble accessing your account? Let us help you, contact support at +1(510) 944-1054 or email@example.com
Forgot password? Reset it here