 8.5.1: Waiting in line The Jefferson Valley Bank once had a separate custo...
 8.5.2: Requirements If we want to use the sample data from Exercise 1 to t...
 8.5.3: Confidence Interval Method of hypothesis Testing Assume that we wan...
 8.5.4: hypothesis Test For the sample data from Exercise 1, we have s = 0....
 8.5.5: Testing Claims about Variation. In Exercises 516, test the given cl...
 8.5.6: Testing Claims about Variation. In Exercises 516, test the given cl...
 8.5.7: Testing Claims about Variation. In Exercises 516, test the given cl...
 8.5.8: Testing Claims about Variation. In Exercises 516, test the given cl...
 8.5.9: Testing Claims about Variation. In Exercises 516, test the given cl...
 8.5.10: Testing Claims about Variation. In Exercises 516, test the given cl...
 8.5.11: Testing Claims about Variation. In Exercises 516, test the given cl...
 8.5.12: Testing Claims about Variation. In Exercises 516, test the given cl...
 8.5.13: Testing Claims about Variation. In Exercises 516, test the given cl...
 8.5.14: Testing Claims about Variation. In Exercises 516, test the given cl...
 8.5.15: Testing Claims about Variation. In Exercises 516, test the given cl...
 8.5.16: Testing Claims about Variation. In Exercises 516, test the given cl...
 8.5.17: Large Data Sets from Appendix B. In Exercises 17 and 18, use the da...
 8.5.18: Large Data Sets from Appendix B. In Exercises 17 and 18, use the da...
 8.5.19: Finding Critical Values of X2 For large numbers of degrees of freed...
 8.5.20: Finding Critical Values of X2 Repeat Exercise 19 using this approxi...
Solutions for Chapter 8.5: Testing a Claim About a Standard Deviation or Variance
Full solutions for Essentials of Statistics  5th Edition
ISBN: 9780321924599
Solutions for Chapter 8.5: Testing a Claim About a Standard Deviation or Variance
Get Full SolutionsEssentials of Statistics was written by and is associated to the ISBN: 9780321924599. Chapter 8.5: Testing a Claim About a Standard Deviation or Variance includes 20 full stepbystep solutions. This expansive textbook survival guide covers the following chapters and their solutions. Since 20 problems in chapter 8.5: Testing a Claim About a Standard Deviation or Variance have been answered, more than 14371 students have viewed full stepbystep solutions from this chapter. This textbook survival guide was created for the textbook: Essentials of Statistics, edition: 5.

Average
See Arithmetic mean.

Binomial random variable
A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.

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).

Combination.
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.

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.

Conidence level
Another term for the conidence coeficient.

Contingency table.
A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria

Continuity correction.
A correction factor used to improve the approximation to binomial probabilities from a normal distribution.

Continuous uniform random variable
A continuous random variable with range of a inite interval and a constant probability density function.

Convolution
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.

Covariance
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 .

Decision interval
A parameter in a tabular CUSUM algorithm that is determined from a tradeoff between false alarms and the detection of assignable causes.

Defect
Used in statistical quality control, a defect is a particular type of nonconformance to speciications or requirements. Sometimes defects are classiied into types, such as appearance defects and functional defects.

Demingâ€™s 14 points.
A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality

Discrete random variable
A random variable with a inite (or countably ininite) range.

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

Error propagation
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.

Geometric mean.
The geometric mean of a set of n positive data values is the nth root of the product of the data values; that is, g x i n i n = ( ) = / w 1 1 .

Harmonic mean
The harmonic mean of a set of data values is the reciprocal of the arithmetic mean of the reciprocals of the data values; that is, h n x i n i = ? ? ? ? ? = ? ? 1 1 1 1 g .