- 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
ISBN: 9781111827045
Probability and Statistics for Engineers and Scientists | 4th Edition - Solutions by Chapter
Get Full SolutionsSince problems from 17 chapters in Probability and Statistics for Engineers and Scientists have been answered, more than 51485 students have viewed full step-by-step answer. The full step-by-step solution to problem in Probability and Statistics for Engineers and Scientists were answered by , our top Statistics solution expert on 01/12/18, 03:07PM. Probability and Statistics for Engineers and Scientists was written by and is associated to the ISBN: 9781111827045. This expansive textbook survival guide covers the following chapters: 17. This textbook survival guide was created for the textbook: Probability and Statistics for Engineers and Scientists, edition: 4.
-
Additivity property of x 2
If two independent random variables X1 and X2 are distributed as chi-square with v1 and v2 degrees of freedom, respectively, Y = + X X 1 2 is a chi-square random variable with u = + v v 1 2 degrees of freedom. This generalizes to any number of independent chi-square random variables.
-
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.
-
Bimodal distribution.
A distribution with two modes
-
C chart
An attribute control chart that plots the total number of defects per unit in a subgroup. Similar to a defects-per-unit or U chart.
-
Center line
A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.
-
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.
-
Completely randomized design (or experiment)
A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.
-
Continuous uniform random variable
A continuous random variable with range of a inite interval and a constant probability density function.
-
Correlation
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.
-
Counting techniques
Formulas used to determine the number of elements in sample spaces and events.
-
Cumulative distribution function
For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.
-
Defect concentration diagram
A quality tool that graphically shows the location of defects on a part or in a process.
-
Defects-per-unit control chart
See U chart
-
Density function
Another name for a probability density function
-
Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.
-
Error of estimation
The difference between an estimated value and the true value.
-
Error propagation
An analysis of how the variance of the random variable that represents that output of a system depends on the variances of the inputs. A formula exists when the output is a linear function of the inputs and the formula is simpliied if the inputs are assumed to be independent.
-
Gamma random variable
A random variable that generalizes an Erlang random variable to noninteger values of the parameter r
-
Gaussian distribution
Another name for the normal distribution, based on the strong connection of Karl F. Gauss to the normal distribution; often used in physics and electrical engineering applications