 3.R3.1: Born to be old? Is there a relationship between the gestational per...
 3.R3.2: Penguins diving A study of king penguins looked for a relationship ...
 3.R3.3: Stats teachers cars A random sample of AP Statistics teachers was a...
 3.R3.4: Late bloomers? Japanese cherry trees tend to blossom early when spr...
 3.R3.5: Whats my grade? In Professor Friedmans economics course, the correl...
 3.R3.6: Calculating achievement The principal of a high school read a study...
 3.T3.1: Section I: Multiple Choice Select the best answer for each question...
 3.T3.2: Section I: Multiple Choice Select the best answer for each question...
 3.T3.3: Section I: Multiple Choice Select the best answer for each question...
 3.T3.4: Section I: Multiple Choice Select the best answer for each question...
 3.T3.5: Section I: Multiple Choice Select the best answer for each question...
 3.T3.6: Section I: Multiple Choice Select the best answer for each question...
 3.T3.7: Section I: Multiple Choice Select the best answer for each question...
 3.T3.8: Section I: Multiple Choice Select the best answer for each question...
 3.T3.9: Section I: Multiple Choice Select the best answer for each question...
 3.T3.10: Section I: Multiple Choice Select the best answer for each question...
 3.T3.11: Section II: Free Response Show all your work. Indicate clearly the ...
 3.T3.12: Section II: Free Response Show all your work. Indicate clearly the ...
 3.T3.13: Section II: Free Response Show all your work. Indicate clearly the ...
Solutions for Chapter 3: Describing Relationships
Full solutions for The Practice of Statistics  5th Edition
ISBN: 9781464108730
Solutions for Chapter 3: Describing Relationships
Get Full SolutionsThis textbook survival guide was created for the textbook: The Practice of Statistics, edition: 5. Chapter 3: Describing Relationships includes 19 full stepbystep solutions. Since 19 problems in chapter 3: Describing Relationships have been answered, more than 11192 students have viewed full stepbystep solutions from this chapter. The Practice of Statistics was written by and is associated to the ISBN: 9781464108730. This expansive textbook survival guide covers the following chapters and their solutions.

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).

All possible (subsets) regressions
A method of variable selection in regression that examines all possible subsets of the candidate regressor variables. Eficient computer algorithms have been developed for implementing all possible regressions

Alternative hypothesis
In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test

Analysis of variance (ANOVA)
A method of decomposing the total variability in a set of observations, as measured by the sum of the squares of these observations from their average, into component sums of squares that are associated with speciic deined sources of variation

Bivariate normal distribution
The joint distribution of two normal random variables

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).

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.

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.

Components of variance
The individual components of the total variance that are attributable to speciic sources. This usually refers to the individual variance components arising from a random or mixed model analysis of variance.

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

Continuity correction.
A correction factor used to improve the approximation to binomial probabilities from a normal distribution.

Contrast
A linear function of treatment means with coeficients that total zero. A contrast is a summary of treatment means that is of interest in an experiment.

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

Design matrix
A matrix that provides the tests that are to be conducted in an experiment.

Discrete uniform random variable
A discrete random variable with a inite range and constant probability mass function.

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

Exhaustive
A property of a collection of events that indicates that their union equals the sample space.

False alarm
A signal from a control chart when no assignable causes are present

Fisherâ€™s least signiicant difference (LSD) method
A series of pairwise hypothesis tests of treatment means in an experiment to determine which means differ.

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