 10.3.1: Explain how to find the critical value for an F@test.
 10.3.2: List five properties of the F@distribution.
 10.3.3: List the three conditions that must be met in order to use a twosa...
 10.3.4: Explain how to determine the values of d.f.N and d.f.D when perform...
 10.3.5: In Exercises 58, find the critical F@value for a righttailed test ...
 10.3.6: In Exercises 58, find the critical F@value for a righttailed test ...
 10.3.7: In Exercises 58, find the critical F@value for a righttailed test ...
 10.3.8: In Exercises 58, find the critical F@value for a righttailed test ...
 10.3.9: In Exercises 9 12, find the critical F@value for a twotailed test ...
 10.3.10: In Exercises 9 12, find the critical F@value for a twotailed test ...
 10.3.11: In Exercises 9 12, find the critical F@value for a twotailed test ...
 10.3.12: In Exercises 9 12, find the critical F@value for a twotailed test ...
 10.3.13: In Exercises 13 18, test the claim about the difference between two...
 10.3.14: In Exercises 13 18, test the claim about the difference between two...
 10.3.15: In Exercises 13 18, test the claim about the difference between two...
 10.3.16: In Exercises 13 18, test the claim about the difference between two...
 10.3.17: In Exercises 13 18, test the claim about the difference between two...
 10.3.18: In Exercises 13 18, test the claim about the difference between two...
 10.3.19: Comparing Two Variances In Exercises 1926, (a) identify the claim a...
 10.3.20: Comparing Two Variances In Exercises 1926, (a) identify the claim a...
 10.3.21: Comparing Two Variances In Exercises 1926, (a) identify the claim a...
 10.3.22: Comparing Two Variances In Exercises 1926, (a) identify the claim a...
 10.3.23: Comparing Two Variances In Exercises 1926, (a) identify the claim a...
 10.3.24: Comparing Two Variances In Exercises 1926, (a) identify the claim a...
 10.3.25: Comparing Two Variances In Exercises 1926, (a) identify the claim a...
 10.3.26: Comparing Two Variances In Exercises 1926, (a) identify the claim a...
 10.3.27: In Exercises 27 and 28, find the right and lefttailed critical F...
 10.3.28: In Exercises 27 and 28, find the right and lefttailed critical F...
 10.3.29: In Exercises 29 and 30, construct the confidence interval for s2 1 ...
 10.3.30: In Exercises 29 and 30, construct the confidence interval for s2 1 ...
Solutions for Chapter 10.3: Comparing Two Variances
Full solutions for Elementary Statistics: Picturing the World  6th Edition
ISBN: 9780321911216
Solutions for Chapter 10.3: Comparing Two Variances
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Chapter 10.3: Comparing Two Variances includes 30 full stepbystep solutions. This textbook survival guide was created for the textbook: Elementary Statistics: Picturing the World , edition: 6. Elementary Statistics: Picturing the World was written by and is associated to the ISBN: 9780321911216. Since 30 problems in chapter 10.3: Comparing Two Variances have been answered, more than 99028 students have viewed full stepbystep solutions from this chapter.

2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

Analytic study
A study in which a sample from a population is used to make inference to a future population. Stability needs to be assumed. See Enumerative study

Assignable cause
The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.

Backward elimination
A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

Biased estimator
Unbiased estimator.

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).

Chisquare (or chisquared) 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.

Chisquare test
Any test of signiicance based on the chisquare distribution. The most common chisquare tests are (1) testing hypotheses about the variance or standard deviation of a normal distribution and (2) testing goodness of it of a theoretical distribution to sample data

Conditional probability distribution
The distribution of a random variable given that the random experiment produces an outcome in an event. The given event might specify values for one or more other random variables

Conditional probability mass function
The probability mass function of the conditional probability distribution of a discrete random variable.

Conidence level
Another term for the conidence coeficient.

Covariance matrix
A square matrix that contains the variances and covariances among a set of random variables, say, X1 , X X 2 k , , … . The main diagonal elements of the matrix are the variances of the random variables and the offdiagonal elements are the covariances between Xi and Xj . Also called the variancecovariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.

Crossed factors
Another name for factors that are arranged in a factorial experiment.

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.

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.

Deining relation
A subset of effects in a fractional factorial design that deine the aliases in the design.

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

Error sum of squares
In analysis of variance, this is the portion of total variability that is due to the random component in the data. It is usually based on replication of observations at certain treatment combinations in the experiment. It is sometimes called the residual sum of squares, although this is really a better term to use only when the sum of squares is based on the remnants of a modelitting process and not on replication.

Finite population correction factor
A term in the formula for the variance of a hypergeometric random variable.

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 .