- 8-5.1: Using Table G, find the critical value(s) for each, show the critic...
- 8-5.2: (ans) Using Table G, find the P-value interval for each x2 test val...
- 8-5.3: Calories in Pancake Syrup A nutritionist claims that the standard d...
- 8-5.4: High Temperatures in January Daily weather observations for southwe...
- 8-5.5: Stolen Aircraft Test the claim that the standard deviation of the n...
- 8-5.6: Carbohydrates in Fast Foods The number of carbohydrates found in a ...
- 8-5.7: Transferring Phone Calls The manager of a large company claims that...
- 8-5.8: Soda Bottle Content A machine fills 12-ounce bottles with soda. For...
- 8-5.9: High-Potassium Foods Potassium is important to good health in keepi...
- 8-5.10: Exam Grades A statistics professor is used to having a variance in ...
- 8-5.11: Tornado Deaths A researcher claims that the standard deviation of t...
- 8-5.12: Interstate Speeds It has been reported that the standard deviation ...
- 8-5.13: College Room and Board Costs Room and board fees for a random sampl...
- 8-5.14: Heights of Volcanoes A sample of heights (in feet) of active volcan...
- 8-5.15: Manufactured Machine Parts A manufacturing process produces machine...
Solutions for Chapter 8-5: x2 Test for a Variance or Standard Deviation
Full solutions for Elementary Statistics: A Step by Step Approach 8th ed. | 8th Edition
2 k p - factorial experiment
A fractional factorial experiment with k factors tested in a 2 ? p fraction with all factors tested at only two levels (settings) each
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.
Asymptotic relative eficiency (ARE)
Used to compare hypothesis tests. The ARE of one test relative to another is the limiting ratio of the sample sizes necessary to obtain identical error probabilities for the two procedures.
An estimator for a parameter obtained from a Bayesian method that uses a prior distribution for the parameter along with the conditional distribution of the data given the parameter to obtain the posterior distribution of the parameter. The estimator is obtained from the posterior distribution.
The joint probability distribution of two random variables.
Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.
The portion of the variability in a set of observations that is due to only random forces and which cannot be traced to speciic sources, such as operators, materials, or equipment. Also called a common cause.
Chi-square (or chi-squared) 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.
Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.
Conditional probability mass function
The probability mass function of the conditional probability distribution of a discrete random variable.
The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.
A probability distribution for a continuous random variable.
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.
Defect concentration diagram
A quality tool that graphically shows the location of defects on a part or in a process.
W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.
The amount of variability exhibited by data
Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.
Error of estimation
The difference between an estimated value and the true value.
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.
An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on