- 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
2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.
The arithmetic mean of a set of numbers x1 , x2 ,…, xn is their sum divided by the number of observations, or ( / )1 1 n xi t n ? = . The arithmetic mean is usually denoted by x , and is often called the average
Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.
An equation for a conditional probability such as PA B ( | ) in terms of the reverse conditional probability PB A ( | ).
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.
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 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.
A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria
Continuous random variable.
A random variable with an interval (either inite or ininite) of real numbers for its range.
A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the in-control value of the parameter that is being monitored and lower and upper control limits. The control limits are determined by statistical criteria and are not arbitrary, nor are they related to speciication limits. If sample points fall within the control limits, the process is said to be in-control, or free from assignable causes. Points beyond the control limits indicate an out-of-control process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.
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 .
Formulas used to determine the number of elements in sample spaces and events.
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.
The value of a statistic corresponding to a stated signiicance level as determined from the sampling distribution. For example, if PZ z PZ ( )( .) . ? =? = 0 025 . 1 96 0 025, then z0 025 . = 1 9. 6 is the critical value of z at the 0.025 level of signiicance. Crossed factors. Another name for factors that are arranged in a factorial experiment.
Another name for factors that are arranged in a factorial experiment.
An expression sometimes used for nonlinear regression models or polynomial regression models.
Distribution free method(s)
Any method of inference (hypothesis testing or conidence interval construction) that does not depend on the form of the underlying distribution of the observations. Sometimes called nonparametric method(s).
The variance of an error term or component in a model.
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.
Fractional factorial experiment
A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.