- Chapter 1:
- Chapter 1: What Is Statistics?
- Chapter 10:
- Chapter 10: Hypothesis Testing
- Chapter 11:
- Chapter 11: Linear Models and Estimation by Least Squares
- Chapter 12:
- Chapter 12: Considerations in Designing Experiments
- Chapter 13:
- Chapter 13: The Analysis of Variance
- Chapter 14:
- Chapter 14: Analysis of Categorical Data
- Chapter 15:
- Chapter 15: Nonparametric Statistics
- Chapter 16:
- Chapter 16: Introduction to Bayesian Methods for Inference
- Chapter 2:
- Chapter 2: Probability
- Chapter 3:
- Chapter 3: Discrete Random Variables and Their Probability Distributions
- Chapter 4:
- Chapter 4: Continuous Variables and Their Probability Distributions
- Chapter 5:
- Chapter 5: Multivariate Probability Distributions
- Chapter 6:
- Chapter 6: Functions of Random Variables
- Chapter 7:
- Chapter 7: Sampling Distributions and the Central Limit Theorem
- Chapter 8:
- Chapter 8: Estimation
- Chapter 9:
- Chapter 9: Properties of Point Estimators and Methods of Estimation
Mathematical Statistics with Applications 7th Edition - Solutions by Chapter
Full solutions for Mathematical Statistics with Applications | 7th Edition
A formula used to determine the probability of the union of two (or more) events from the probabilities of the events and their intersection(s).
All possible (subsets) regressions
A method of variable selection in regression that examines all possible subsets of the candidate regressor variables. Eficient computer algorithms have been developed for implementing all possible regressions
A distribution with two modes
The joint probability distribution of two random variables.
Box plot (or box and whisker plot)
A graphical display of data in which the box contains the middle 50% of the data (the interquartile range) with the median dividing it, and the whiskers extend to the smallest and largest values (or some deined lower and upper limits).
The probability of an event given that the random experiment produces an outcome in another event.
The variance of the conditional probability distribution of a random variable.
A two-dimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.
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 .
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
The amount of variability exhibited by data
Error mean square
The error sum of squares divided by its number of degrees of freedom.
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.
The expected value of a random variable X is its long-term average or mean value. In the continuous case, the expected value of X is E X xf x dx ( ) = ?? ( ) ? ? where f ( ) x is the density function of the random variable X.
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.
Finite population correction factor
A term in the formula for the variance of a hypergeometric random variable.
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
Fixed factor (or fixed effect).
In analysis of variance, a factor or effect is considered ixed if all the levels of interest for that factor are included in the experiment. Conclusions are then valid about this set of levels only, although when the factor is quantitative, it is customary to it a model to the data for interpolating between these levels.