 3.1: Statistical Literacy (a) What measures of variation indicate spread...
 3.2: Critical Thinking Look at the two histograms below. Each involves t...
 3.3: Critical Thinking Consider the following Minitab display of two dat...
 3.4: Consumer: Radon Gas Radon: The One Wants to Face is the title of an...
 3.5: Political Science: Georgia Democrats How Democratic is Georgia? Cou...
 3.6: Grades: Weighted Average Professor Cramer determines a final grade ...
 3.7: General: Average Weight An elevator is loaded with 16 people and is...
 3.8: Agriculture: Harvest Weight of Maize The following data represent w...
 3.9: Focus Problem: The Educational Advantage Solve the focus problem at...
 3.10: (a) Make a boxandwhisker plot of the data. Find the interquartile...
 3.11: Performance Rating: Weighted Average A performance evaluation for n...
Solutions for Chapter 3: Organizing Data
Full solutions for Understandable Statistics  9th Edition
ISBN: 9780618949922
Solutions for Chapter 3: Organizing Data
Get Full SolutionsThis textbook survival guide was created for the textbook: Understandable Statistics, edition: 9. Since 11 problems in chapter 3: Organizing Data have been answered, more than 33263 students have viewed full stepbystep solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 3: Organizing Data includes 11 full stepbystep solutions. Understandable Statistics was written by and is associated to the ISBN: 9780618949922.

`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).

Addition rule
A formula used to determine the probability of the union of two (or more) events from the probabilities of the events and their intersection(s).

Attribute
A qualitative characteristic of an item or unit, usually arising in quality control. For example, classifying production units as defective or nondefective results in attributes data.

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

Causal variable
When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable

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.

Coeficient of determination
See R 2 .

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

Consistent estimator
An estimator that converges in probability to the true value of the estimated parameter as the sample size increases.

Continuous random variable.
A random variable with an interval (either inite or ininite) of real numbers for its range.

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

Counting techniques
Formulas used to determine the number of elements in sample spaces and events.

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

Defectsperunit control chart
See U chart

Dependent variable
The response variable in regression or a designed experiment.

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.

Expected value
The expected value of a random variable X is its longterm average or mean value. In the continuous case, the expected value of X is E X xf x dx ( ) = ?? ( ) ? ? where f ( ) x is the density function of the random variable X.

Firstorder model
A model that contains only irstorder terms. For example, the irstorder response surface model in two variables is y xx = + ?? ? ? 0 11 2 2 + + . A irstorder model is also called a main effects model

Generator
Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.

Hat matrix.
In multiple regression, the matrix H XXX X = ( ) ? ? 1 . This a projection matrix that maps the vector of observed response values into a vector of itted values by yˆ = = X X X X y Hy ( ) ? ? ?1 .