Explanation Calculation: Step-by-step procedure to generate 200 random samples using the MINITAB software: Click on Calc > Random Data > Binomial Distribution . In Number of rows of data to generate section, enter 200 . In the Store in column , enter column C1 named as Random Numbers . For Number of trails , enter 50 . For Probability , enter 0.6 . Click OK .. Output using the MINITAB is given below: Random number 27 28 31 41 26 33 22 29 23 31 26 28 29 32 27 31 29 31 29 27 29 31 29 34 28 32 30 31 28 28 29 30 26 30 37 30 23 33 26 33 31 28 32 28 29 36 31 30 31 30 29 27 33 31 28 36 30 27 27 33 32 32 33 27 27 31 31 29 29 25 28 30 25 24 31 25 31 31 27 32 31 30 33 27 24 30 32 35 29 32 32 26 24 28 25 29 30 27 31 32 28 29 26 33 32 32 34 26 28 32 35 32 29 32 32 35 32 26 27 26 26 35 27 31 28 27 32 30 30 34 32 34 24 29 32 37 24 24 24 24 26 26 34 27 30 31 30 26 30 31 31 27 24 35 32 30 28 27 27 22 34 31 33 24 34 31 35 27 33 28 33 28 33 27 25 31 31 26 31 29 32 28 28 35 27 29 30 39 29 34 24 25 29 33 26 29 34 35 34 32 From the Standard Normal Table, the z value for 90% level is 1.645. The general formula for the confidence interval for the binomial parameter is, p ^ ± z 1 − α 2 p ^ q ^ n The lower bound and upper bound is tabulated below: Random Numbers p ^ q ^ = 1 − p ^ z 1 − α 2 S E = z 1 − α 2 p ^ q ^ n Lower bound Upper bound 27 0.54 0.46 1.645 0.1159 0.4241 0.6559 26 0.52 0.48 1.645 0.1162 0.4038 0.6362 29 0.58 0.42 1.645 0.1148 0.4652 0.6948 29 0.58 0.42 1.645 0.1148 0.4652 0.6948 31 0.62 0.38 1.645 0.1129 0.5071 0.7329 29 0.58 0.42 1.645 0.1148 0.4652 0.6948 32 0.64 0.36 1.645 0.1117 0.5283 0.7517 28 0.56 0.44 1.645 0.1155 0.4445 0.6755 31 0.62 0.38 1.645 0.1129 0.5071 0.7329 32 0.64 0.36 1.645 0.1117 0.5283 0.7517 28 0.56 0.44 1.645 0.1155 0.4445 0.6755 35 0.7 0.3 1.645 0.1066 0.5934 0.8066 26 0.52 0.48 1.645 0.1162 0.4038 0.6362 32 0.64 0.36 1.645 0.1117 0.5283 0.7517 26 0.52 0.48 1.645 0.1162 0.4038 0.6362 31 0.62 0.38 1.645 0.1129 0.5071 0.7329 34 0.68 0.32 1.645 0.1085 0.5715 0.7885 33 0.66 0.34 1.645 0.1102 0.5498 0.7702 32 0.64 0.36 1.645 0.1117 0.5283 0.7517 24 0.48 0.52 1.645 0.1162 0.3638 0.5962 28 0.56 0.44 1.645 0.1155 0.4445 0.6755 28 0.56 0.44 1.645 0.1155 0.4445 0.6755 31 0.62 0.38 1.645 0.1129 0.5071 0.7329 30 0.6 0.4 1.645 0.1140 0.4860 0.7140 28 0.56 0.44 1.645 0.1155 0.4445 0.6755 27 0.54 0.46 1.645 0.1159 0.4241 0.6559 32 0.64 0.36 1.645 0.1117 0.5283 0.7517 30 0.6 0.4 1.645 0.1140 0.4860 0.7140 30 0.6 0.4 1.645 0.1140 0.4860 0.7140 26 0.52 0.48 1.645 0.1162 0.4038 0.6362 29 0.58 0.42 1.645 0.1148 0.4652 0.6948 32 0.64 0.36 1.645 0.1117 0.5283 0.7517 35 0.7 0.3 1.645 0.1066 0.5934 0.8066 34 0.68 0.32 1.645 0.1085 0.5715 0.7885 26 0.52 0.48 1.645 0.1162 0.4038 0.6362 27 0.54 0.46 1.645 0.1159 0.4241 0.6559 31 0.62 0.38 1.645 0.1129 0.5071 0.7329 28 0.56 0.44 1.645 0.1155 0.4445 0.6755 28 0.56 0.44 1.645 0.1155 0.4445 0.6755 25 0.5 0.5 1.645 0.1163 0.3837 0.6163 31 0.62 0.38 1.645 0.1129 0.5071 0.7329 29 0.58 0.42 1.645 0.1148 0.4652 0.6948 29 0.58 0.42 1.645 0.1148 0.4652 0.6948 26 0.52 0.48 1.645 0.1162 0.4038 0.6362 32 0.64 0.36 1.645 0.1117 0.5283 0.7517 33 0.66 0.34 1.645 0.1102 0.5498 0.7702 33 0.66 0.34 1.645 0.1102 0.5498 0.7702 25 0.5 0.5 1.645 0.1163 0.3837 0.6163 33 0.66 0.34 1.645 0.1102 0.5498 0.7702 24 0.48 0.52 1.645 0.1162 0.3638 0.5962 26 0.52 0.48 1.645 0.1162 0.4038 0.6362 29 0.58 0.42 1.645 0.1148 0.4652 0.6948 27 0.54 0.46 1.645 0.1159 0.4241 0.6559 24 0.48 0.52 1.645 0.1162 0.3638 0.5962 34 0.68 0.32 1.645 0.1085 0.5715 0.7885 24 0.48 0.52 1.645 0.1162 0.3638 0.5962 33 0.66 0.34 1.645 0.1102 0.5498 0.7702 33 0.66 0.34 1.645 0.1102 0.5498 0.7702 28 0.56 0.44 1.645 0.1155 0.4445 0.6755 29 0.58 0.42 1.645 0.1148 0.4652 0.6948 41 0.82 0.18 1.645 0.0894 0.7306 0.9094 32 0.64 0.36 1.645 0.1117 0.5283 0.7517 34 0.68 0.32 1.645 0.1085 0.5715 0.7885 30 0.6 0.4 1.645 0.1140 0.4860 0.7140 28 0.56 0.44 1.645 0.1155 0.4445 0.6755 31 0.62 0.38 1.645 0.1129 0.5071 0.7329 27 0.54 0.46 1.645 0.1159 0.4241 0.6559 24 0.48 0.52 1.645 0.1162 0.3638 0.5962 27 0.54 0.46 1.645 0.1159 0.4241 0.6559 28 0.56 0.44 1.645 0.1155 0.4445 0.6755 33 0.66 0.34 1.645 0.1102 0.5498 0.7702 32 0.64 0.36 1.645 0.1117 0.5283 0.7517 31 0.62 0.38 1.645 0.1129 0.5071 0.7329 29 0.58 0.42 1.645 0.1148 0.4652 0.6948 27 0.54 0.46 1.645 0.1159 0.4241 0.6559 35 0.7 0.3 1.645 0.1066 0.5934 0.8066 24 0.48 0.52 1.645 0.1162 0.3638 0.5962 27 0.54 0.46 1.645 0.1159 0.4241 0.6559 35 0.7 0.3 1.645 0.1066 0.5934 0.8066 33 0.66 0.34 1.645 0.1102 0.5498 0.7702 26 0.52 0.48 1.645 0.1162 0.4038 0.6362 27 0.54 0.46 1.645 0.1159 0.4241 0.6559 28 0.56 0.44 1.645 0

8th Edition

ISBN: 9781305268920

Author: Bernard Rosner

Publisher: Cengage Learning

See similar textbooks

Concept explainers

Continuous Probability Distributions

Probability distributions are of two types, which are continuous probability distributions and discrete probability distributions. A continuous probability distribution contains an infinite number of values. For example, if time is infinite: you could co…

Normal Distribution

Suppose we had to design a bathroom weighing scale, how would we decide what should be the range of the weighing machine? Would we take the highest recorded human weight in history and use that as the upper limit for our weighing scale? This may not be a…

Videos

Question

Chapter 6, Problem 95P

To determine

Obtain the percentage of the Cis include the parameter for a binomial distribution with n=50and p=0.6.

Expert Solution & Answer

Want to see the full answer?

Check out a sample textbook solution

See solution

Chapter 6, Problem 94P

Chapter 6, Problem 96P

Students have asked these similar questions

Consider the ceocomp dataset of compensation information for the CEO’s of 100 U.S. companies. We wish to fit aregression model to assess the relationship between CEO compensation in thousands of dollars (includes salary andbonus, but not stock gains) and the following variates:AGE: The CEOs age, in yearsEDUCATN: The CEO’s education level (1 = no college degree; 2 = college/undergrad. degree; 3 = grad. degree)BACKGRD: Background type(1= banking/financial; 2 = sales/marketing; 3 = technical; 4 = legal; 5 = other)TENURE: Number of years employed by the firmEXPER: Number of years as the firm CEOSALES: Sales revenues, in millions of dollarsVAL: Market value of the CEO's stock, in natural logarithm unitsPCNTOWN: Percentage of firm's market value owned by the CEOPROF: Profits of the firm, before taxes, in millions of dollars1) Create a scatterplot matrix for this dataset. Briefly comment on the observed relationships between compensationand the other variates.Note that companies with negative…

6 (Model Selection, Estimation and Prediction of GARCH) Consider the daily returns rt of General Electric Company stock (ticker: "GE") from "2021-01-01" to "2024-03-31", comprising a total of 813 daily returns. Using the "fGarch" package of R, outputs of fitting three GARCH models to the returns are given at the end of this question. Model 1 ARCH (1) with standard normal innovations; Model 2 Model 3 GARCH (1, 1) with Student-t innovations; GARCH (2, 2) with Student-t innovations; Based on the outputs, answer the following questions. (a) What can be inferred from the Standardized Residual Tests conducted on Model 1? (b) Which model do you recommend for prediction between Model 2 and Model 3? Why? (c) Write down the fitted model for the model that you recommended in Part (b). (d) Using the model recommended in Part (b), predict the conditional volatility in the next trading day, specifically trading day 814.

4 (MLE of ARCH) Suppose rt follows ARCH(2) with E(rt) = 0, rt = ut, ut = στει, σε where {+} is a sequence of independent and identically distributed (iid) standard normal random variables. With observations r₁,...,, write down the log-likelihood function for the model esti- mation.

Chapter 6 Solutions

Fundamentals of Biostatistics

Ch. 6.5 - What is the difference between a standard...Ch. 6.5 - What does a 95% CI mean?Ch. 6 - Suppose we are asked to construct a list of...Ch. 6 - Suppose we are asked to construct a list of...Ch. 6 - Suppose we are asked to construct a list of...Ch. 6 - Suppose we are asked to construct a list of...Ch. 6 - The data in Table 6.10 concern the mean triceps...Ch. 6 - The data in Table 6.10 concern the mean triceps...Ch. 6 - The data in Table 6.10 concern the mean triceps...Ch. 6 - The data in Table 6.10 concern the mean triceps...

Ch. 6 - The data in Table 6.10 concern the mean triceps...Ch. 6 - The data in Table 6.10 concern the mean triceps...Ch. 6 - Refer to the data in Table 2.13. Regard this...Ch. 6 - Refer to the data in Table 2.13. Regard this...Ch. 6 - Refer to the data in Table 2.13. Regard this...Ch. 6 - Refer to the data in Table 2.13. Regard this...Ch. 6 - Refer to the data in Table 2.13. Regard this...Ch. 6 - Refer to the data in Table 2.13. Regard this...Ch. 6 - Refer to the data in Table 2.13. Regard this...Ch. 6 - A nine-laboratory cooperative study was performed...Ch. 6 - A nine-laboratory cooperative study was performed...Ch. 6 - A nine-laboratory cooperative study was performed...Ch. 6 - A nine-laboratory cooperative study was performed...Ch. 6 - A nine-laboratory cooperative study was performed...Ch. 6 - A study of psychological and physiological health...Ch. 6 - A study of psychological and physiological health...Ch. 6 - A study is conducted to test the hypothesis that...Ch. 6 - A study is conducted to test the hypothesis that...Ch. 6 - Suppose a clinical trial is conducted to test the...Ch. 6 - Suppose a clinical trial is conducted to test the...Ch. 6 - Suppose a clinical trial is conducted to test the...Ch. 6 - Suppose we want to estimate the concentration...Ch. 6 - Suppose we want to estimate the concentration...Ch. 6 - Suppose we want to estimate the concentration...Ch. 6 - Much discussion has taken place concerning...Ch. 6 - Much discussion has taken place concerning...Ch. 6 - Much discussion has taken place concerning...Ch. 6 - A new assay is developed to obtain the...Ch. 6 - A new assay is developed to obtain the...Ch. 6 - A new assay is developed to obtain the...Ch. 6 - A new assay is developed to obtain the...Ch. 6 - Suppose 100 hypertensive people are given an...Ch. 6 - Suppose 100 hypertensive people are given an...Ch. 6 - Suppose 100 hypertensive people are given an...Ch. 6 - Suppose we decide a better measure of the...Ch. 6 - Suppose we decide a better measure of the...Ch. 6 - Suppose we decide a better measure of the...Ch. 6 - Suppose we decide a better measure of the...Ch. 6 - Draw six random samples of size 5 from the data in...Ch. 6 - Draw six random samples of size 5 from the data in...Ch. 6 - Draw six random samples of size 5 from the data in...Ch. 6 - Draw six random samples of size 5 from the data in...Ch. 6 - Draw six random samples of size 5 from the data in...Ch. 6 - Figure 6.4b (p. 172) plotted the sampling...Ch. 6 - Figure 6.4b (p. 172) plotted the sampling...Ch. 6 - Figure 6.4b (p. 172) plotted the sampling...Ch. 6 - Figure 6.4b (p. 172) plotted the sampling...Ch. 6 - The etiology of high blood pressure remains a...Ch. 6 - The etiology of high blood pressure remains a...Ch. 6 - The etiology of high blood pressure remains a...Ch. 6 - Data Set SEXRAT.DAT, at www.cengagebrain.com,...Ch. 6 - A cohort of hemophiliacs is followed to elicit...Ch. 6 - A cohort of hemophiliacs is followed to elicit...Ch. 6 - A cohort of hemophiliacs is followed to elicit...Ch. 6 - We have previously described Data Set LEAD.DAT (at...Ch. 6 - We have previously described Data Set LEAD.DAT (at...Ch. 6 - We have previously described Data Set LEAD.DAT (at...Ch. 6 - Data Set NIFED.DAT (at www.cengagebrain.com) was...Ch. 6 - Data Set NIFED.DAT (at www.cengagebrain.com) was...Ch. 6 - Data Set NIFED.DAT (at www.cengagebrain.com) was...Ch. 6 - Suppose that there are 6 deaths due to bladder...Ch. 6 - Suppose that there are 4 deaths due to stomach...Ch. 6 - The value of mammography as a screening test for...Ch. 6 - The value of mammography as a screening test for...Ch. 6 - The value of mammography as a screening test for...Ch. 6 - The value of mammography as a screening test for...Ch. 6 - On the computer, draw 1000 bootstrap samples of...Ch. 6 - On the computer, draw 1000 bootstrap samples of...Ch. 6 - A study was performed to investigate the...Ch. 6 - A study was performed to investigate the...Ch. 6 - Refer to Data Set BONEDEN.DAT at...Ch. 6 - Refer to Data Set BONEDEN.DAT at...Ch. 6 - Prob. 88P Ch. 6 - Prob. 89P Ch. 6 - Prob. 90P Ch. 6 - Prob. 91P Ch. 6 - Prob. 92P Ch. 6 - Prob. 93P Ch. 6 - Prob. 94P Ch. 6 - Prob. 95P Ch. 6 - Prob. 96P Ch. 6 - A patient who is taking antihypertensive...Ch. 6 - A patient who is taking antihypertensive...Ch. 6 - A patient who is taking antihypertensive...Ch. 6 - A patient who is taking antihypertensive...Ch. 6 - A patient who is taking antihypertensive...Ch. 6 - Injuries are common in football and may be related...Ch. 6 - Injuries are common in football and may be related...Ch. 6 - A hypertensive patient has been on...Ch. 6 - A hypertensive patient has been on...Ch. 6 - A hypertensive patient has been on...Ch. 6 - A hypertensive patient has been on...Ch. 6 - A radiologist investigates whether a new (less...Ch. 6 - A radiologist investigates whether a new (less...Ch. 6 - The estimation of allele probabilities is...Ch. 6 - The estimation of allele probabilities is...Ch. 6 - The estimation of allele probabilities is...Ch. 6 - As an experiment, 10,000 people are completely...Ch. 6 - As an experiment, 10,000 people are completely...Ch. 6 - Which of the following sample results yields a 95%...Ch. 6 - Suppose we observe 30 cases of colon cancer over...

Knowledge Booster

$Statistics$

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.

Obtain the percentage of the Cis include the parameter for a binomial distribution with n = 50 and p = 0.6 .

Concept explainers

Videos

Obtain the percentage of the Cis include the parameter for a binomial distribution with n=50and p=0.6.

Want to see the full answer?

Chapter 6 Solutions