Statistics for Business and Economics (13th Edition)
13th Edition
ISBN: 9780134506593
Author: James T. McClave, P. George Benson, Terry Sincich
Publisher: PEARSON
expand_more
expand_more
format_list_bulleted
Textbook Question
Chapter 5.3, Problem 5.16LM
Suppose a random sample of n = 25 measurements is selected from a population with
- a. µ = 10, σ = 3
- b. µ, = 100, σ = 25
- c. µ − 20, σ − 40
- d. µ = 10, σ = 100
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
22
Bob decides that after his heart attack is a
good time to get in shape, so he starts exer-
cising each day and plans to increase his
exercise time as he goes along. Look at the
two line graphs shown in the following fig-
ures. One is a good representation of his
data, and the other should get as much use
as Bob's treadmill before his heart attack.
Exercise time
40
Line Graph 1 of Exercise Log
35
30-
25
201
20
Exercise time
80
80
60
40-
1
10 20
30
30
40 50 60
Day
170
50
80
Line Graph 2 of Exercise Log
1
10 20
90 100
30
30 40 50 60 70 80 90 100
Day
a. Compare the two graphs. Do they repre-
sent the same data set, or do they show
totally different data sets?
b. Assume that both graphs are made from
the same data. Which graph is more
appropriate and why?
8
Suppose that a small town has five people
with a rare form of cancer. Does this auto-
matically mean a huge problem exists that
needs to be addressed?
1
M&Ms colors come in the following percent-
ages: 13 percent brown, 14 percent yellow,
13 percent red, 24 percent blue, 20 percent
orange, and 16 percent green. Reach into a
bag of M&Ms without looking.
a. What's the chance that you pull out a
brown or yellow M&M?
b. What's the chance that you won't pull
out a blue? sw
Chapter 5 Solutions
Statistics for Business and Economics (13th Edition)
Ch. 5.1 - The probability distribution shown here describes...Ch. 5.1 - Consider the population described by the...Ch. 5.1 - Refer to Exercise 5.3 and find E (x) = Then use...Ch. 5.1 - Refer to Exercise 5.3. Assume that a random sample...Ch. 5.1 - In Example 5.3 we used a computer to generate 1...Ch. 5.2 - Consider the following probability distribution: x...Ch. 5.2 - Consider the following probability distribution: x...Ch. 5.2 - Consider the following probability distribution: x...Ch. 5.2 - Refer to Exercise 5.31. a. Show that x is an...Ch. 5.2 - Refer to Exercise 5.3. a. Find the sampling...
Ch. 5.2 - Refer to Exercise 5.5, in which we found the...Ch. 5.3 - Will the sampling distribution of x always be...Ch. 5.3 - Suppose a random sample of n = 25 measurements is...Ch. 5.3 - Suppose a random sample of n measurements is...Ch. 5.3 - A random sample of n = 64 observations is drawn...Ch. 5.3 - Refer to Exercise 5.18. Find the probability that...Ch. 5.3 - A random sample of n = 900 observations is...Ch. 5.3 - A random sample of n = 100 observations is...Ch. 5.3 - Open the applet Sampling Distributions. On the...Ch. 5.3 - Open the applet Sampling Distributions. On the...Ch. 5.3 - Voltage sags and swells. Refer to the Electrical...Ch. 5.3 - Salary of a travel management professional....Ch. 5.3 - Corporate sustainability of CPA firms. Refer to...Ch. 5.3 - Critical-part failures in NASCAR vehicles. Refer...Ch. 5.3 - Tomato as a taste modifier. Miraculin is a protein...Ch. 5.3 - Prob. 5.28ACICh. 5.3 - Levelness of concrete slabs. Geotechnical...Ch. 5.3 - Video game players and divided attention tasks....Ch. 5.3 - Exposure to a chemical in Teflon-coated cookware....Ch. 5.3 - Rental car fleet evaluation. National Car Rental...Ch. 5.3 - Prob. 5.34ACACh. 5.3 - Handwashing vs. handrubbing. The British Medical...Ch. 5.4 - Suppose a random sample of n measurements is...Ch. 5.4 - Suppose a random sample of n = 500 measurements is...Ch. 5.4 - A random sample of n = 80 measurements is drawn...Ch. 5.4 - A random sample of n = 250 measurements is drawn...Ch. 5.4 - A random sample of n = 1, 500 measurements is...Ch. 5.4 - Consider a population with values of x equal to 0...Ch. 5.4 - Dentists use of laughing gas. According to the...Ch. 5.4 - Cable TV subscriptions and cord cutters ....Ch. 5.4 - Do social robots walk or roll? Refer to the...Ch. 5.4 - Working on summer vacation. According to a Harris...Ch. 5.4 - Hospital work-related injuries. According to an...Ch. 5.4 - Hotel guest satisfaction. Refer to the results of...Ch. 5.4 - Stock market participation and IQ. Refer to The...Ch. 5.4 - Fingerprint expertise. Refer to the Psychological...Ch. 5.4 - Who prepares your tax return? As part of a study...Ch. 5.4 - Apps not working on smartphone. In a survey titled...Ch. 5 - The standard deviation (or, as it is usually...Ch. 5 - Consider a sample statistic A. As with all sample...Ch. 5 - A random sample of 40 observations is to be drawn...Ch. 5 - A random sample of n = 68 observations is selected...Ch. 5 - A random sample of n = 500 observations is...Ch. 5 - A random sample of n = 300 observations is...Ch. 5 - Use a statistical software package to generate 100...Ch. 5 - Use a statistical software package to generate 100...Ch. 5 - Suppose x equals the number of heads observed when...Ch. 5 - A random sample of size n is to be drawn from a...Ch. 5 - Requests to a Web server. In Exercise 4.175 (p....Ch. 5 - Improving SAT scores. Refer to the Chance (Winter...Ch. 5 - Study of why EMS workers leave the job. A study of...Ch. 5 - Downloading apps to your cell phone. Refer to...Ch. 5 - Surface roughness of pipe. Refer to the...Ch. 5 - Analysis of supplier lead time. Lead time is the...Ch. 5 - Producing machine bearings. To determine whether a...Ch. 5 - Quality control. Refer to Exercise 5.68. The mean...Ch. 5 - Length of job tenure. Researchers at the Terry...Ch. 5 - Switching banks after a merger. Banks that merge...Ch. 5 - Piercing rating of fencing safety jackets. A...Ch. 5 - Errors in filling prescriptions A large number of...Ch. 5 - Purchasing decision. A building contractor has...Ch. 5 - Motivation of drug dealers. Refer to the Applied...Ch. 5 - Soft-drink bottles. A soft-drink bottler purchases...
Knowledge Booster
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.Similar questions
- 11. Prove or disprove: (a) If is a characteristic function, then so is ²; (b) If is a non-negative characteristic function, then so is √√4.arrow_forward4. Suppose that P(X = 1) = P(X = -1) = 1/2, that Y = U(-1, 1) and that X and Y are independent. (a) Show, by direct computation, that X + Y = U(-2, 2). (b) Translate the result to a statement about characteristic functions. (c) Which well-known trigonometric formula did you discover?arrow_forward9. The concentration function of a random variable X is defined as Qx(h) = sup P(x ≤ X ≤x+h), h>0. x (a) Show that Qx+b (h) = Qx(h). (b) Is it true that Qx(ah) =aQx(h)? (c) Show that, if X and Y are independent random variables, then Qx+y (h) min{Qx(h). Qy (h)). To put the concept in perspective, if X1, X2, X, are independent, identically distributed random variables, and S₁ = Z=1Xk, then there exists an absolute constant, A, such that A Qs, (h) ≤ √n Some references: [79, 80, 162, 222], and [204], Sect. 1.5.arrow_forward
- 29 Suppose that a mound-shaped data set has a must mean of 10 and standard deviation of 2. a. About what percentage of the data should lie between 6 and 12? b. About what percentage of the data should lie between 4 and 6? c. About what percentage of the data should lie below 4? 91002 175/1 3arrow_forward2,3, ample and rical t? the 28 Suppose that a mound-shaped data set has a mean of 10 and standard deviation of 2. a. About what percentage of the data should lie between 8 and 12? b. About what percentage of the data should lie above 10? c. About what percentage of the data should lie above 12?arrow_forward27 Suppose that you have a data set of 1, 2, 2, 3, 3, 3, 4, 4, 5, and you assume that this sample represents a population. The mean is 3 and g the standard deviation is 1.225.10 a. Explain why you can apply the empirical rule to this data set. b. Where would "most of the values" in the population fall, based on this data set?arrow_forward
- 30 Explain how you can use the empirical rule to find out whether a data set is mound- shaped, using only the values of the data themselves (no histogram available).arrow_forward5. Let X be a positive random variable with finite variance, and let A = (0, 1). Prove that P(X AEX) 2 (1-A)² (EX)² EX2arrow_forward6. Let, for p = (0, 1), and xe R. X be a random variable defined as follows: P(X=-x) = P(X = x)=p. P(X=0)= 1-2p. Show that there is equality in Chebyshev's inequality for X. This means that Chebyshev's inequality, in spite of being rather crude, cannot be improved without additional assumptions.arrow_forward
- 4. Prove that, for any random variable X, the minimum of EIX-al is attained for a = med (X).arrow_forward8. Recall, from Sect. 2.16.4, the likelihood ratio statistic, Ln, which was defined as a product of independent, identically distributed random variables with mean 1 (under the so-called null hypothesis), and the, sometimes more convenient, log-likelihood, log L, which was a sum of independent, identically distributed random variables, which, however, do not have mean log 1 = 0. (a) Verify that the last claim is correct, by proving the more general statement, namely that, if Y is a non-negative random variable with finite mean, then E(log Y) log(EY). (b) Prove that, in fact, there is strict inequality: E(log Y) < log(EY), unless Y is degenerate. (c) Review the proof of Jensen's inequality, Theorem 5.1. Generalize with a glimpse on (b).arrow_forward3. Prove that, for any random variable X, the minimum of E(X - a)² is attained for a = EX. Provedarrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw HillBig Ideas Math A Bridge To Success Algebra 1: Stu...AlgebraISBN:9781680331141Author:HOUGHTON MIFFLIN HARCOURTPublisher:Houghton Mifflin HarcourtMathematics For Machine TechnologyAdvanced MathISBN:9781337798310Author:Peterson, John.Publisher:Cengage Learning,
Glencoe Algebra 1, Student Edition, 9780079039897...
Algebra
ISBN:9780079039897
Author:Carter
Publisher:McGraw Hill
Big Ideas Math A Bridge To Success Algebra 1: Stu...
Algebra
ISBN:9781680331141
Author:HOUGHTON MIFFLIN HARCOURT
Publisher:Houghton Mifflin Harcourt
Mathematics For Machine Technology
Advanced Math
ISBN:9781337798310
Author:Peterson, John.
Publisher:Cengage Learning,
Hypothesis Testing using Confidence Interval Approach; Author: BUM2413 Applied Statistics UMP;https://www.youtube.com/watch?v=Hq1l3e9pLyY;License: Standard YouTube License, CC-BY
Hypothesis Testing - Difference of Two Means - Student's -Distribution & Normal Distribution; Author: The Organic Chemistry Tutor;https://www.youtube.com/watch?v=UcZwyzwWU7o;License: Standard Youtube License