 9.1: Driving for Pleasure Two groups of drivers are surveyed to see how ...
 9.2: Average Earnings of College Graduates The average yearly earnings o...
 9.3: Communication Times According to the Bureau of Labor StatisticsAmer...
 9.4: Average Temperatures The average temperatures for a 25day period f...
 9.5: Teachers Salaries A sample of 15 teachers from Rhode Island has an ...
 9.6: Soft Drinks in School The data show the amounts (in thousands of do...
 9.7: High and Low Temperatures March is a month of variable weather in t...
 9.8: Automobile Part Production In an effort to increase production of a...
 9.9: Lay Teachers in Religious Schools A study found a slightly lower pe...
 9.10: Adopted Pets According to the 20052006 National Pet Owners Survey, ...
 9.11: Noise Levels in Hospitals In the hospital study cited previously, t...
 9.12: Heights of World Famous Cathedrals The heights (in feet) for a rand...
 9.13: Paint Prices Two large home improvement stores advertise that they ...
 9.14: Cholesterol Levels A researcher wishes to see if there is a differe...
 9.15: Apartment Rental Fees The data shown are the rental fees (in dollar...
 9.16: Prices of LowCalorie Foods The average price of a sample of 12 bot...
 9.17: Jet Ski Accidents The data shown represent the number of accidents ...
 9.18: Salaries of Chemists A sample of 12 chemists from Washington state ...
 9.19: Family Incomes The average income of 15 families who reside in a la...
 9.20: Mathematical Skills In an effort to improve the mathematical skills...
 9.21: Egg Production To increase egg production, a farmer decided to incr...
 9.22: Factory Worker Literacy Rates In a sample of 80 workers from a fact...
 9.23: Male Head of Household Arecent survey of 200 households showed that...
 9.24: Money Spent on Road Repair A politician wishes to compare the varia...
 9.25: Heights of Basketball Players A researcher wants to compare the var...
Solutions for Chapter 9: Review Execises
Full solutions for Elementary Statistics: A Step by Step Approach 8th ed.  8th Edition
ISBN: 9780073386102
Solutions for Chapter 9: Review Execises
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Elementary Statistics: A Step by Step Approach 8th ed. was written by and is associated to the ISBN: 9780073386102. Chapter 9: Review Execises includes 25 full stepbystep solutions. This textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach 8th ed., edition: 8. Since 25 problems in chapter 9: Review Execises have been answered, more than 34767 students have viewed full stepbystep solutions from this chapter.

`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).

aerror (or arisk)
In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).

Arithmetic mean
The arithmetic mean of a set of numbers x1 , x2 ,…, xn is their sum divided by the number of observations, or ( / )1 1 n xi t n ? = . The arithmetic mean is usually denoted by x , and is often called the average

Axioms of probability
A set of rules that probabilities deined on a sample space must follow. See Probability

Chance cause
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.

Completely randomized design (or experiment)
A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.

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

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

Contour plot
A twodimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

Control limits
See Control chart.

Correction factor
A term used for the quantity ( / )( ) 1 1 2 n xi i n ? = that is subtracted from xi i n 2 ? =1 to give the corrected sum of squares deined as (/ ) ( ) 1 1 2 n xx i x i n ? = i ? . The correction factor can also be written as nx 2 .

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 .

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.

Cumulative normal distribution function
The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.

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

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 of estimation
The difference between an estimated value and the true value.

Extra sum of squares method
A method used in regression analysis to conduct a hypothesis test for the additional contribution of one or more variables to a model.

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 .