Pearson eText for Probability and Stati...10th EditionRobert Hogg, Elliot Tanis Publisher: PEARSON+ISBN: 9780137538461
Pearson eText for Probability and Stati...
Solutions for Pearson eText for Probability and Statistical Inference -- Instant Access (Pearson+)
Problem 1E:
An excellent free-throw shooter attempts several free throws until she misses. (a) If p = 0.9 is her...Problem 2E:
Show that 63512 is the probability that the fifth head is observed on the tenth independent flip of...Problem 3E:
Suppose that a basketball player different from the ones in Example 2.6-2 and in Exercise 2.6-1 can...Problem 4E:
Suppose an airport metal detector catches a person with metal 99% of the time. That is. it misses...Problem 5E:
Let the moment-generating function M(t) of X exist for hth. Consider the function R(t)=lnM(t). The...Problem 6E:
Use the result of Exercise 2.6-5 to find the mean and variance of the (a) Bernoulli distribution....Problem 8E:
The probability that a companys workforce has no accidents in a given month is 0.7. The numbers of...Browse All Chapters of This Textbook
Chapter 1.1 - Properties Of ProbabilityChapter 1.2 - Methods Of EnumerationChapter 1.3 - Conditional ProbabilityChapter 1.4 - Independent EventsChapter 1.5 - Bayes’ TheoremChapter 2.1 - Random Variables Of The Discrete TypeChapter 2.2 - Mathematical ExpectationChapter 2.3 - Special Mathematical ExpectationsChapter 2.4 - The Binomial DistributionChapter 2.5 - The Hypergeometric Distribution
Chapter 2.6 - The Negative Binomial DistributionChapter 2.7 - The Poisson DistributionChapter 3.1 - Random Variables Of The Continuous TypeChapter 3.2 - The Exponential, Gamma, And Chi-square DistributionsChapter 3.3 - The Normal DistributionChapter 3.4 - Additional ModelsChapter 4.1 - Bivariate Distributions Of The Discrete TypeChapter 4.2 - The Correlation CoefficientChapter 4.3 - Conditional DistributionsChapter 4.4 - Bivariate Distributions Of The ContinuoustypeChapter 4.5 - The Bivariate Normal DistributionChapter 5.1 - Functions Of One Random VariableChapter 5.2 - Transformations Of Two Random VariablesChapter 5.3 - Several Independent Random VariablesChapter 5.4 - The Moment-generating Function TechniqueChapter 5.5 - Random Functions Associated With Normal DistributionsChapter 5.6 - The Central Limit TheoremChapter 5.7 - Approximations For Discrete DistributionsChapter 5.8 - Chebyshev’s Inequality And Convergence In ProbabilityChapter 5.9 - Limiting Moment-generating FunctionsChapter 7.2 - Confidence Intervals For The Difference Of Two MeansChapter 8.1 - Tests About One Mean
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Probability and Statistical Inference
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