- Chapter 1: Probability
- Chapter 10: Summarizing Data
- Chapter 11: Comparing Two Samples
- Chapter 12: The Analysis of Variance
- Chapter 13: The Analysis of Categorical Data
- Chapter 14: Linear Least Squares
- Chapter 2: Random Variables
- Chapter 3: Joint Distributions
- Chapter 4: Expected Values
- Chapter 5: Limit Theorems
- Chapter 6: Distributions Derived from the Normal Distribution
- Chapter 7: Survey Sampling
- Chapter 8: Estimation of Parameters and Fitting of Probability Distributions
- Chapter 9: Testing Hypotheses and Assessing Goodness of Fit
Mathematical Statistics and Data Analysis 3rd Edition - Solutions by Chapter
Full solutions for Mathematical Statistics and Data Analysis | 3rd Edition
2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.
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
Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.
See Arithmetic mean.
Chi-square (or chi-squared) random variable
A continuous random variable that results from the sum of squares of independent standard normal random variables. It is a special case of a gamma random variable.
Coeficient of determination
See R 2 .
Continuous uniform random variable
A continuous random variable with range of a inite interval and a constant probability density function.
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.
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).
A measure of association between two random variables obtained as the expected value of the product of the two random variables around their means; that is, Cov(X Y, ) [( )( )] =? ? E X Y ? ? X Y .
Deming’s 14 points.
A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality
A model to relate a response to one or more regressors or factors that is developed from data obtained from the system.
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.
A subset of a sample space.
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.
The distribution of the random variable deined as the ratio of two independent chi-square random variables, each divided by its number of degrees of freedom.
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.
In statistical quality control, that portion of a number of units or the output of a process that is defective.
Gamma random variable
A random variable that generalizes an Erlang random variable to noninteger values of the parameter r
A function that is used to determine properties of the probability distribution of a random variable. See Moment-generating function