 5.1.1E: What is the probability of an event that is impossible? Suppose tha...
 5.1.1: What is the probability of an event that is impossible? Suppose tha...
 5.1.2E: What does it mean for an event to be unusual? Why should the cutoff...
 5.1.2: What does it mean for an event to be unusual? Why should the cutoff...
 5.1.3E: True or False: In a probability model, the sum of the probabilities...
 5.1.3: True or False: In a probability model, the sum of the probabilities...
 5.1.4E: True or False: Probability is a measure of the likelihood of a rand...
 5.1.4: True or False: Probability is a measure of the likelihood of a rand...
 5.1.5E: In probability, a(n)__________ is any process that can be repeated ...
 5.1.5: In probability, a(n)_________ is any process that can be repeated i...
 5.1.6E: A(n)__________is any collection of outcomes from a probability expe...
 5.1.6: A(n) ________ is any collection of outcomes from a probability expe...
 5.1.7E: Verify that the following is a probability model. What do we call t...
 5.1.7: A(n) ________ is any collection of outcomes from a probability expe...
 5.1.8E: Verify that the following is a probability model. If the model repr...
 5.1.8: Verify that the following is a probability model. If the model repr...
 5.1.9E: Why is the following not a probability model?ColorProbabilityRed0.3...
 5.1.9: Why is the following not a probability model? Color Probability Red...
 5.1.10E: Why is the following not a probability model?ColorProbabilityRed0.1...
 5.1.10: Why is the following not a probability model? Color ProbabilityRed ...
 5.1.11E: Which of the following numbers could be the probability of an event...
 5.1.11: Which of the following numbers could be the probability of an event...
 5.1.12E: Which of the following numbers could be the probability of an event?
 5.1.12: Which of the following numbers could be the probability of an event...
 5.1.13E: In fivecard stud poker, a player is dealt five cards. The probabil...
 5.1.13: In fivecard stud poker, a player is dealt five cards. The probabil...
 5.1.14E: In sevencard stud poker, a player is dealt seven cards. The probab...
 5.1.14: In sevencard stud poker, a player is dealt seven cards. The probab...
 5.1.15E: Suppose that you toss a coin 100 times and get 95 heads and 5 tails...
 5.1.15: Suppose that you toss a coin 100 times and get 95 heads and 5 tails...
 5.1.16: Suppose that you roll a die 100 times and get six 80 times. Based o...
 5.1.16E: Suppose that you roll a die 100 times and get six 80 times. Based o...
 5.1.17: Bob is asked to construct a probability model for rolling a pair of...
 5.1.17E: Bob is asked to construct a probability model for rolling a pair of...
 5.1.18: Blood Types A person can have one of four blood types: A, B, AB, or...
 5.1.18E: Blood Types A person can have one of four blood types: A, B, AB, or...
 5.1.19: If a person rolls a sixsided die and then flips a coin, describe t...
 5.1.19E: If a person rolls a sixsided die and then flips a coin, describe t...
 5.1.20: If a basketball player shoots three free throws, describe the sampl...
 5.1.20E: If a basketball player shoots three free throws, describe the sampl...
 5.1.21: According to the U.S. Department of Education, 42.8% of 3yearolds...
 5.1.21E: According to the U.S. Department of Education, 42.8% of 3yearolds...
 5.1.22: According to the American Veterinary Medical Association, the propo...
 5.1.22E: According to the American Veterinary Medical Association, the propo...
 5.1.23: For 2326, let the sample space be S = {1, 2, 3, 4, 5, 6, 7, 8, 9, 1...
 5.1.23E: Let the sample space be S = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}. Suppos...
 5.1.24: For 2326, let the sample space be S = {1, 2, 3, 4, 5, 6, 7, 8, 9, 1...
 5.1.24E: Let the sample space be S = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}. Suppos...
 5.1.25: For 2326, let the sample space be S = {1, 2, 3, 4, 5, 6, 7, 8, 9, 1...
 5.1.25E: Let the sample space be S = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}. Suppos...
 5.1.26: For 2326, let the sample space be S = {1, 2, 3, 4, 5, 6, 7, 8, 9, 1...
 5.1.26E: Let the sample space be S = {1, 2, 3, 4, 5, 6, 7, 8, 9, 10}. Suppos...
 5.1.27: Play Sports? A survey of 500 randomly selected high school students...
 5.1.27E: Play Sports? A survey of 500 randomly selected high school students...
 5.1.28: Volunteer? In a survey of 1100 female adults (18 years of age or ol...
 5.1.28E: Volunteer? In a survey of 1100 female adults (18 years of age or ol...
 5.1.29: Planting Tulips A bag of 100 tulip bulbs purchased from a nursery c...
 5.1.29E: Planting Tulips A bag of 100 tulip bulbs purchased from a nursery c...
 5.1.30: Golf Balls The local golf store sells an onion bag that contains 80...
 5.1.30E: Golf Balls The local golf store sells an “onion bag” that contains ...
 5.1.31: Roulette In the game of roulette, a wheel consists of 38 slots numb...
 5.1.31E: Roulette In the game of roulette, a wheel consists of 38 slots numb...
 5.1.32: Birthdays Exclude leap years from the following calculations and as...
 5.1.32E: Birthdays Exclude leap years from the following calculations and as...
 5.1.33: Genetics A gene is composed of two alleles. An allele can be either...
 5.1.33E: Genetics A gene is composed of two alleles. An allele can be either...
 5.1.34: More Genetics In 33, we learned that for some diseases, such as sic...
 5.1.34E: More Genetics In learned that for some diseases, such as sicklecel...
 5.1.35: College Survey In a national survey conducted by the Centers for Di...
 5.1.35E: College Survey In a national survey conducted by the Centers for Di...
 5.1.36: College Survey In a national survey conducted by the Centers for Di...
 5.1.36E: College SurveyIn a national survey conducted by the Centers for Dis...
 5.1.37: Larceny Theft A police officer randomly selected 642 police records...
 5.1.37E: Larceny TheftA police officer randomly selected 642 police records ...
 5.1.38: Multiple Births The following data represent the number of live mul...
 5.1.38E: Multiple BirthsThe following data represent the number of live mult...
 5.1.39: 3942 use the given table, which lists six possible assignments of p...
 5.1.39E: Use the given table, which lists six possible assignments of probab...
 5.1.40: 3942 use the given table, which lists six possible assignments of p...
 5.1.40E: Use the given table, which lists six possible assignments of probab...
 5.1.41: 3942 use the given table, which lists six possible assignments of p...
 5.1.41E: Use the given table, which lists six possible assignments of probab...
 5.1.42: 3942 use the given table, which lists six possible assignments of p...
 5.1.42E: Use the given table, which lists six possible assignments of probab...
 5.1.43: Going to Disney World John, Roberto, Clarice, Dominique, and Marco ...
 5.1.43E: Going to Disney World John, Roberto, Clarice, Dominique, and Marco ...
 5.1.44: Six Flags In 2011, Six Flags St. Louis had ten roller coasters: The...
 5.1.44E: Six Flags In 2011, Six Flags St. Louis had ten roller coasters: The...
 5.1.45: Barry Bonds On October 5, 2001, Barry Bonds broke Mark McGwires hom...
 5.1.45E: Barry Bonds On October 5, 2001, Barry Bonds broke Mark McGwire’s ho...
 5.1.46: Rolling a Die (a) Roll a single die 50 times, recording the result ...
 5.1.46E: Rolling a Die(a) Roll a single die 50 times, recording the result o...
 5.1.47: Simulation Use a graphing calculator or statistical software to sim...
 5.1.47E: Simulation Use a graphing calculator or statistical software to sim...
 5.1.48: Classifying Probability Determine whether the probabilities on the ...
 5.1.48E: Classifying Probability Determine whether the probabilities on the ...
 5.1.49: Checking for Loaded Dice You suspect a pair of dice to be loaded an...
 5.1.49E: Checking for Loaded DiceYou suspect a pair of dice to be loaded and...
 5.1.50: Conduct a survey in your school by randomly asking 50 students whet...
 5.1.50E: Conduct a survey in your school by randomly asking 50 students whet...
 5.1.51: In 2006, the median income of families in the United States was $58...
 5.1.51E: In 2006, the median income of families in the United States was $58...
 5.1.52: The middle 50% of enrolled freshmen at Washington University in St....
 5.1.52E: The middle 50% of enrolled freshmen at Washington University in St....
 5.1.53: Sullivan Survey Choose a qualitative variable from the Sullivan Sur...
 5.1.53E: Sullivan Survey Choose a qualitative variable from the Sullivan Sur...
 5.1.54: Putting It Together: Drug Side Effects In placebocontrolled clinica...
 5.1.54E: Putting It Together: Drug Side EffectsIn placebocontrolled clinica...
 5.1.55: Explain the Law of Large Numbers. How does this law apply to gambli...
 5.1.55E: Explain the Law of Large Numbers. How does this law apply to gambli...
 5.1.56: In computing classical probabilities, all outcomes must be equally ...
 5.1.56E: In computing classical probabilities, all outcomes must be equally ...
 5.1.57: Describe what an unusual event is. Should the same cutoff always be...
 5.1.57E: Describe what an unusual event is. Should the same cutoff always be...
 5.1.58: You are planning a trip to a water park tomorrow. The weather forec...
 5.1.58E: You are planning a trip to a water park tomorrow. The weather forec...
 5.1.59: Describe the difference between classical and empirical probability.
 5.1.59E: Describe the difference between classical and empirical probability.
 5.1.60: Ask Marilyn In a September 19, 2010, article in Parade Magazine wri...
 5.1.60E: Ask Marilyn In a September 19, 2010, article in Parade Magazine wri...
Solutions for Chapter 5.1: PROBABILITY RULES
Full solutions for Statistics: Informed Decisions Using Data  4th Edition
ISBN: 9780321757272
Solutions for Chapter 5.1: PROBABILITY RULES
Get Full SolutionsThis textbook survival guide was created for the textbook: Statistics: Informed Decisions Using Data , edition: 4. This expansive textbook survival guide covers the following chapters and their solutions. Statistics: Informed Decisions Using Data was written by and is associated to the ISBN: 9780321757272. Since 120 problems in chapter 5.1: PROBABILITY RULES have been answered, more than 141023 students have viewed full stepbystep solutions from this chapter. Chapter 5.1: PROBABILITY RULES includes 120 full stepbystep solutions.

Acceptance region
In hypothesis testing, a region in the sample space of the test statistic such that if the test statistic falls within it, the null hypothesis cannot be rejected. This terminology is used because rejection of H0 is always a strong conclusion and acceptance of H0 is generally a weak conclusion

Additivity property of x 2
If two independent random variables X1 and X2 are distributed as chisquare with v1 and v2 degrees of freedom, respectively, Y = + X X 1 2 is a chisquare random variable with u = + v v 1 2 degrees of freedom. This generalizes to any number of independent chisquare random variables.

Assignable cause
The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.

Backward elimination
A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

Bayes’ theorem
An equation for a conditional probability such as PA B (  ) in terms of the reverse conditional probability PB A (  ).

Central composite design (CCD)
A secondorder response surface design in k variables consisting of a twolevel factorial, 2k axial runs, and one or more center points. The twolevel factorial portion of a CCD can be a fractional factorial design when k is large. The CCD is the most widely used design for itting a secondorder model.

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

Conidence level
Another term for the conidence coeficient.

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

Cumulative distribution function
For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.

Density function
Another name for a probability density function

Designed experiment
An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

Discrete distribution
A probability distribution for a discrete random variable

Distribution function
Another name for a cumulative distribution function.

Eficiency
A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.

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

Fraction defective control chart
See P chart

Frequency distribution
An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on