 5.4.1: The notation P(F E) means the probability of event given event . 2
 5.4.1E: The notation P(FE) means the probability of event______given event...
 5.4.2: If P(E) = 0.6 and P(E F) = 0.34, are events E and F independent?
 5.4.2E: If P(E) = 0.6 and P(EF) = 0.34, are events E and F independent?
 5.4.3: Suppose that E and F are two events and that P(E and F) = 0.6 and P...
 5.4.3E: Suppose that E and F are two events and that P(E and F) = 0.6 and P...
 5.4.4: Suppose that E and F are two events and that P(E and F) = 0.21 and ...
 5.4.4E: Suppose that E and F are two events and that P(E and F) = 0.21 and ...
 5.4.5: Suppose that E and F are two events and that N(E and F ) = 420 and ...
 5.4.5E: Suppose that E and F are two events and that N(E and F ) = 420 and ...
 5.4.6: Suppose that E and F are two events and that N(E and F) = 380 and N...
 5.4.6E: Suppose that E and F are two events and that N(E and F) = 380 and N...
 5.4.7: Suppose that E and F are two events and that P(E) = 0.8 and P(F E) ...
 5.4.7E: Suppose that E and F are two events and that P(E) = 0.8 and P(F\ E)...
 5.4.8: Suppose that E and F are two events and that P(E) = 0.4 and P(F E) ...
 5.4.8E: Suppose that E and F are two events and that P(E) = 0.4 and P(F\ E)...
 5.4.9: According to the U.S. Census Bureau, the probability that a randoml...
 5.4.9E: According to the U.S. Census Bureau, the probability that a randoml...
 5.4.10: The probability that a randomly selected individual in the United S...
 5.4.10E: The probability that a randomly selected individual in the United S...
 5.4.11: Drawing a Card Suppose that a single card is selected from a standa...
 5.4.11E: Drawing a Card Suppose that a single card is selected from a standa...
 5.4.12: Drawing a Card Suppose that a single card is selected from a standa...
 5.4.12E: Drawing a Card Suppose that a single card is selected from a standa...
 5.4.13: Rainy Days For the month of June in the city of Chicago, 37% of the...
 5.4.13E: Rainy Days For the month of June in the city of Chicago, 37% of the...
 5.4.14: Cause of Death According to the U.S. National Center for Health Sta...
 5.4.14E: Cause of Death According to the U.S. National Center for Health Sta...
 5.4.15: High School Dropouts According to the U.S. Census Bureau, 8.0% of 1...
 5.4.15E: High School Dropouts According to the U.S. Census Bureau, 8.0% of 1...
 5.4.16E: Income by Region According to the U.S. Census Bureau, 17.9% of U.S....
 5.4.16: Income by Region According to the U.S. Census Bureau, 17.9% of U.S....
 5.4.17E: Made in America In a recent Harris Poll, a random sample of adult A...
 5.4.17: Made in America In a recent Harris Poll, a random sample of adult A...
 5.4.18: Sullivan Survey: Speeding Tickets The following data represent the ...
 5.4.18E: Sullivan Survey: Speeding TicketsThe following data represent the n...
 5.4.19E: Traffic FatalitiesThe following data represent the number of traffi...
 5.4.19: Traffic Fatalities The following data represent the number of traff...
 5.4.20E: Driver FatalitiesThe following data represent the number of drivers...
 5.4.20: Driver Fatalities The following data represent the number of driver...
 5.4.21E: Acceptance Sampling Suppose that you just received a shipment of si...
 5.4.21: Acceptance Sampling Suppose that you just received a shipment of si...
 5.4.22E: Committee A committee consists of four women and three men. The com...
 5.4.22: Committee A committee consists of four women and three men. The com...
 5.4.23E: Suppose that two cards are randomly selected from a standard 52car...
 5.4.23: Suppose that two cards are randomly selected from a standard 52car...
 5.4.24E: Suppose that two cards are randomly selected from a standard 52car...
 5.4.24: Suppose that two cards are randomly selected from a standard 52car...
 5.4.25E: Board Work This past semester, I had a small business calculus sect...
 5.4.25: Board Work This past semester, I had a small business calculus sect...
 5.4.26E: Party My wife has organized a monthly neighborhood party. Five peop...
 5.4.26: Party My wife has organized a monthly neighborhood party. Five peop...
 5.4.27E: Playing a CD on the Random Setting Suppose that a compact disc (CD)...
 5.4.27: Playing a CD on the Random Setting Suppose that a compact disc (CD)...
 5.4.28E: Packaging Error Due to a manufacturing error, three cans of regular...
 5.4.28: Packaging Error Due to a manufacturing error, three cans of regular...
 5.4.29E: Planting Tulips A bag of 30 tulip bulbs purchased from a nursery co...
 5.4.29: Planting Tulips A bag of 30 tulip bulbs purchased from a nursery co...
 5.4.30E: Golf Balls The local golf store sells an “onion bag” that contains ...
 5.4.30: Golf Balls The local golf store sells an onion bag that contains 35...
 5.4.31E: Smokers According to the National Center for Health Statistics, the...
 5.4.31: Smokers According to the National Center for Health Statistics, the...
 5.4.32E: Multiple Jobs According to the U.S. Bureau of Labor Statistics, the...
 5.4.32: Multiple Jobs According to the U.S. Bureau of Labor Statistics, the...
 5.4.33E: The Birthday the probability that at least 2 people in a room of 10...
 5.4.33: The Birthday the probability that at least 2 people in a room of 10...
 5.4.34E: The Birthday the procedure given in Problem, compute the probabilit...
 5.4.34: The Birthday the procedure given in 33, compute the probability tha...
 5.4.35E: Teen CommunicationThe following data represent the number of differ...
 5.4.35: The Birthday the procedure given in 33, compute the probability tha...
 5.4.36E: Party AffiliationThe following data represent political party by ag...
 5.4.36: Party Affiliation The following data represent political party by a...
 5.4.37E: A Flush A flush in the card game of poker occurs if a player gets f...
 5.4.37: A Flush A flush in the card game of poker occurs if a player gets f...
 5.4.38E: A Royal Flush A royal flush in the game of poker occurs if the play...
 5.4.38: A Royal Flush A royal flush in the game of poker occurs if the play...
 5.4.39E: Independence in Small Samples from Large PopulationsSuppose that a ...
 5.4.39: Independence in Small Samples from Large Populations Suppose that a...
 5.4.40E: Independence in Small Samples from Large Populations Suppose that a...
 5.4.40: ndependence in Small Samples from Large Populations Suppose that a ...
 5.4.41E: Independent?Refer to the contingency table in relates age and likel...
 5.4.41: Independent? Refer to the contingency table in that relates age and...
 5.4.42E: Independent?Refer to the contingency table in relates number of spe...
 5.4.42: Independent? Refer to the contingency table in that relates number ...
 5.4.43E: Independent?Refer to the contingency table in relates person type i...
 5.4.43: Independent? Refer to the contingency table in that relates person ...
 5.4.44E: Independent?Refer to the contingency table in relates gender to day...
 5.4.44: Independent? Refer to the contingency table in that relates gender ...
 5.4.45E: Let’s Make a Deal In 1991, columnist Marilyn Vos Savant posted her ...
 5.4.45: Lets Make a Deal In 1991, columnist Marilyn Vos Savant posted her r...
Solutions for Chapter 5.4: CONDITIONAL PROBABILITY AND THE GENERAL MULTIPLICATION RULE
Full solutions for Statistics: Informed Decisions Using Data  4th Edition
ISBN: 9780321757272
Solutions for Chapter 5.4: CONDITIONAL PROBABILITY AND THE GENERAL MULTIPLICATION RULE
Get Full SolutionsChapter 5.4: CONDITIONAL PROBABILITY AND THE GENERAL MULTIPLICATION RULE includes 90 full stepbystep solutions. This expansive textbook survival guide covers the following chapters and their solutions. Since 90 problems in chapter 5.4: CONDITIONAL PROBABILITY AND THE GENERAL MULTIPLICATION RULE have been answered, more than 154869 students have viewed full stepbystep solutions from this chapter. This textbook survival guide was created for the textbook: Statistics: Informed Decisions Using Data , edition: 4. Statistics: Informed Decisions Using Data was written by and is associated to the ISBN: 9780321757272.

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).

Bayes’ estimator
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.

Bernoulli trials
Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

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

Block
In experimental design, a group of experimental units or material that is relatively homogeneous. The purpose of dividing experimental units into blocks is to produce an experimental design wherein variability within blocks is smaller than variability between blocks. This allows the factors of interest to be compared in an environment that has less variability than in an unblocked experiment.

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

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

Cook’s distance
In regression, Cook’s distance is a measure of the inluence of each individual observation on the estimates of the regression model parameters. It expresses the distance that the vector of model parameter estimates with the ith observation removed lies from the vector of model parameter estimates based on all observations. Large values of Cook’s distance indicate that the observation is inluential.

Correlation coeficient
A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

Correlation matrix
A square matrix that contains the correlations among a set of random variables, say, XX X 1 2 k , ,…, . The main diagonal elements of the matrix are unity and the offdiagonal elements rij are the correlations between Xi and Xj .

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 .

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

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

Defect concentration diagram
A quality tool that graphically shows the location of defects on a part or in a process.

Discrete distribution
A probability distribution for a discrete random variable

Enumerative study
A study in which a sample from a population is used to make inference to the population. See Analytic study

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

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

Goodness of fit
In general, the agreement of a set of observed values and a set of theoretical values that depend on some hypothesis. The term is often used in itting a theoretical distribution to a set of observations.