- Chapter 1: Statistics: The Art and Science of Data
- Chapter 10: Inference in Practice
- Chapter 2: Describing Distributions of Data
- Chapter 3: Modeling Distributions of Data
- Chapter 4: Describing Relationships
- Chapter 5: Sampling and Surveys
- Chapter 6: Designing Experiments
- Chapter 7: Probability: What Are the Chances?
- Chapter 8: Probability Models
- Chapter 9: ntroduction to Inference
Statistics Through Applications 2nd Edition - Solutions by Chapter
Full solutions for Statistics Through Applications | 2nd Edition
In hypothesis testing, a region in the sample space of the test statistic such that if the test statistic falls within it, the null hypothesis cannot be rejected. This terminology is used because rejection of H0 is always a strong conclusion and acceptance of H0 is generally a weak conclusion
In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test
When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable
A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.
Central composite design (CCD)
A second-order response surface design in k variables consisting of a two-level factorial, 2k axial runs, and one or more center points. The two-level factorial portion of a CCD can be a fractional factorial design when k is large. The CCD is the most widely used design for itting a second-order model.
Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.
Continuous random variable.
A random variable with an interval (either inite or ininite) of real numbers for its range.
A two-dimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.
A subset of effects in a fractional factorial design that deine the aliases in the design.
W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.
A matrix that provides the tests that are to be conducted in an experiment.
The amount of variability exhibited by data
A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.
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.
Any test of signiicance involving the F distribution. The most common F-tests are (1) testing hypotheses about the variances or standard deviations of two independent normal distributions, (2) testing hypotheses about treatment means or variance components in the analysis of variance, and (3) testing signiicance of regression or tests on subsets of parameters in a regression model.
A type of experimental design in which every level of one factor is tested in combination with every level of another factor. In general, in a factorial experiment, all possible combinations of factor levels are tested.
Fraction defective control chart
See P chart
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.
A function used in the probability density function of a gamma random variable that can be considered to extend factorials
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