 9.3.1: Statistical Literacy To use the normal distribution to test a propo...
 9.3.2: Statistical Literacy Consider a binomial experiment with n trials a...
 9.3.3: Critical Thinking In general, if sample data are such that the null...
 9.3.4: Critical Thinking An article in a newspaper states that the proport...
 9.3.5: Focus Problem: Benfords Law Please read the Focus the beginning of ...
 9.3.6: Focus Problem: Benfords Law Again suppose you are the auditor for a...
 9.3.7: Sociology: Crime Rate Is the national crime rate really going down?...
 9.3.8: College Athletics: Graduation Rate Women athletes at the University...
 9.3.9: Highway Accidents: DUI The U.S. Department of Transportation, Natio...
 9.3.10: Preference: Color What is your favorite color? A large survey of co...
 9.3.11: Wildlife: Wolves The following is based on information from The Wol...
 9.3.12: Fishing: Northern Pike Athabasca Fishing Lodge is located on Lake A...
 9.3.13: Platos Republic: Syllable Patterns Prose rhythm is characterized as...
 9.3.14: Platos Dialogues: Prose Rhythm Symposium is part of a larger work r...
 9.3.15: . Consumers: Product Loyalty USA Today reported that about 47% of t...
 9.3.16: Supermarket: Prices Harpers Index reported that 80% of all supermar...
 9.3.17: Medical: Hypertension This problem is based on information taken fr...
 9.3.18: Medical: Hypertension Diltiazem is a commonly prescribed drug for h...
 9.3.19: MyersBriggs: Extroverts Are most student government leaders extrov...
 9.3.20: Critical Region Method: Testing Proportions Solve using the critica...
 9.3.21: Critical Region Method: Testing Proportions Solve using the critica...
 9.3.22: Critical Region Method: Testing Proportions Solve using the critica...
Solutions for Chapter 9.3: HYPOTHESIS TESTING
Full solutions for Understandable Statistics  9th Edition
ISBN: 9780618949922
Solutions for Chapter 9.3: HYPOTHESIS TESTING
Get Full SolutionsSince 22 problems in chapter 9.3: HYPOTHESIS TESTING have been answered, more than 38181 students have viewed full stepbystep solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 9.3: HYPOTHESIS TESTING includes 22 full stepbystep solutions. Understandable Statistics was written by and is associated to the ISBN: 9780618949922. This textbook survival guide was created for the textbook: Understandable Statistics, edition: 9.

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

`error (or `risk)
In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.

Average run length, or ARL
The average number of samples taken in a process monitoring or inspection scheme until the scheme signals that the process is operating at a level different from the level in which it began.

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

Center line
A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.

Central limit theorem
The simplest form of the central limit theorem states that the sum of n independently distributed random variables will tend to be normally distributed as n becomes large. It is a necessary and suficient condition that none of the variances of the individual random variables are large in comparison to their sum. There are more general forms of the central theorem that allow ininite variances and correlated random variables, and there is a multivariate version of the theorem.

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

Coeficient of determination
See R 2 .

Conditional probability
The probability of an event given that the random experiment produces an outcome in another event.

Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.

Control chart
A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the incontrol value of the parameter that is being monitored and lower and upper control limits. The control limits are determined by statistical criteria and are not arbitrary, nor are they related to speciication limits. If sample points fall within the control limits, the process is said to be incontrol, or free from assignable causes. Points beyond the control limits indicate an outofcontrol process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.

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.

Cumulative sum control chart (CUSUM)
A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t

Estimate (or point estimate)
The numerical value of a point estimator.

Forward selection
A method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.

Fraction defective
In statistical quality control, that portion of a number of units or the output of a process that is defective.

Generating function
A function that is used to determine properties of the probability distribution of a random variable. See Momentgenerating function

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 .