Concept explainers
(a)
The description about the population distribution.
(a)
Answer to Problem 16E
The population distribution is approximately a binomial distribution with p = 0.75.
Explanation of Solution
Given information:
Number of white beads = 1000
Number of red beads = 3000
Number of beads for SRS = 50
Standard deviation = 0.06
To find the total population, add the number of white beads and red beads that is, 1000 beads and 3000 beads.
Find the proportion of red beads by dividing 3000 by 4000.
The above population distribution is approximately a binomial distribution with
Hence, the population distribution is approximately a binomial distribution with p = 0.75.
(b)
The description about the sampling distribution of
(b)
Explanation of Solution
Given information:
Number of white beads = 1000
Number of red beads = 3000
Number of beads for SRS = 50
Mean of the Normal distribution = 0.75
Standard deviation = 0.06
The values of sample proportion
This means that the sampling distribution of
Also, in the given data the sampling distribution of
The sampling distribution differs from the population distribution by its Normal distribution.
Chapter 7 Solutions
The Practice of Statistics for AP - 4th Edition
Additional Math Textbook Solutions
A First Course in Probability (10th Edition)
Thinking Mathematically (6th Edition)
College Algebra (7th Edition)
University Calculus: Early Transcendentals (4th Edition)
Calculus: Early Transcendentals (2nd Edition)
- During busy political seasons, many opinion polls are conducted. In apresidential race, how do you think the participants in polls are generally selected?Discuss any issues regarding simple random, stratified, systematic, cluster, andconvenience sampling in these polls. What about other types of polls, besides political?arrow_forwardPlease could you explain why 0.5 was added to each upper limpit of the intervals.Thanksarrow_forward28. (a) Under what conditions do we say that two random variables X and Y are independent? (b) Demonstrate that if X and Y are independent, then it follows that E(XY) = E(X)E(Y); (e) Show by a counter example that the converse of (ii) is not necessarily true.arrow_forward
- 19. Let X be a non-negative random variable. Show that lim nE (IX >n)) = 0. E lim (x)-0. = >arrow_forward(c) Utilize Fubini's Theorem to demonstrate that E(X)= = (1- F(x))dx.arrow_forward(c) Describe the positive and negative parts of a random variable. How is the integral defined for a general random variable using these components?arrow_forward
- MATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons IncProbability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage LearningStatistics for The Behavioral Sciences (MindTap C...StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage Learning
- Elementary Statistics: Picturing the World (7th E...StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSONThe Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. FreemanIntroduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman