 6.11.1: A random sample of size 11 from a normal distribution has variance ...
 6.11.2: A random sample of size 29 from a normal distribution has variance ...
 6.11.3: Scores on an IQ test are normally distributed. A sample of 25 IQ sc...
 6.11.4: A machine that fills beverage cans is supposed to put 12 ounces of ...
 6.11.5: A sample of 25 oneyearold girls had a mean weight of 24.1 pounds ...
 6.11.6: The 2008 General Social Survey asked a large number of people how m...
 6.11.7: Scores on the math SAT are normally distributed. A sample of 20 SAT...
 6.11.8: One of the ways in which doctors try to determine how long a single...
 6.11.9: Find the upper 5% point of F7,20.
 6.11.10: Find the upper 1% point of F2,5.
 6.11.11: An F test with five degrees of freedom in the numerator and seven d...
 6.11.12: A broth used to manufacture a pharmaceutical product has its sugar ...
 6.11.13: Refer to Exercise 11 in Section 5.6. Can you conclude that the vari...
 6.11.14: Refer to Exercise 13 in Section 5.6. Can you conclude that the time...
Solutions for Chapter 6.11: Tests for Variances of Normal Populations
Full solutions for Statistics for Engineers and Scientists  4th Edition
ISBN: 9780073401331
Solutions for Chapter 6.11: Tests for Variances of Normal Populations
Get Full SolutionsSince 14 problems in chapter 6.11: Tests for Variances of Normal Populations have been answered, more than 285893 students have viewed full stepbystep solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Statistics for Engineers and Scientists , edition: 4. Statistics for Engineers and Scientists was written by and is associated to the ISBN: 9780073401331. Chapter 6.11: Tests for Variances of Normal Populations includes 14 full stepbystep solutions.

Acceptance region
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

Adjusted R 2
A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

Alias
In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

Alternative hypothesis
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

Bias
An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest.

Coeficient of determination
See R 2 .

Confounding
When a factorial experiment is run in blocks and the blocks are too small to contain a complete replicate of the experiment, one can run a fraction of the replicate in each block, but this results in losing information on some effects. These effects are linked with or confounded with the blocks. In general, when two factors are varied such that their individual effects cannot be determined separately, their effects are said to be confounded.

Conidence coeficient
The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.

Critical region
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.

Defectsperunit control chart
See U chart

Degrees of freedom.
The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.

Dependent variable
The response variable in regression or a designed experiment.

Design matrix
A matrix that provides the tests that are to be conducted in an experiment.

Designed experiment
An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

Empirical model
A model to relate a response to one or more regressors or factors that is developed from data obtained from the system.

Error mean square
The error sum of squares divided by its number of degrees of freedom.

Error variance
The variance of an error term or component in a model.

F distribution.
The distribution of the random variable deined as the ratio of two independent chisquare random variables, each divided by its number of degrees of freedom.

Ftest
Any test of signiicance involving the F distribution. The most common Ftests 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.

Gamma function
A function used in the probability density function of a gamma random variable that can be considered to extend factorials