STATISTICAL TECHNIQUES IN BUSINESS AND E
18th Edition
ISBN: 9781260570489
Author: Lind
Publisher: MCG
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Chapter 3, Problem 51E
a.
To determine
Find the sample variance.
b.
To determine
Find the sample standard deviation.
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Chapter 3 Solutions
STATISTICAL TECHNIQUES IN BUSINESS AND E
Ch. 3 - The annual incomes of a sample of...Ch. 3 - The six students in Computer Science 411 are a...Ch. 3 - Compute the mean of the following population...Ch. 3 - Compute the mean of the following population...Ch. 3 - a. Compute the mean of the following sample...Ch. 3 - a. Compute the mean of the following sample...Ch. 3 - Compute the mean of the following sample values:...Ch. 3 - Suppose you go to the grocery store and spend...Ch. 3 - For Exercises 710, (a) compute the arithmetic mean...Ch. 3 - For Exercises 710, (a) compute the arithmetic mean...
Ch. 3 - For Exercises 710, (a) compute the arithmetic mean...Ch. 3 - For Exercises 710, (a) compute the arithmetic mean...Ch. 3 - Prob. 11ECh. 3 - Prob. 12ECh. 3 - Prob. 2.1SRCh. 3 - Prob. 2.2SRCh. 3 - Prob. 13ECh. 3 - Prob. 14ECh. 3 - Prob. 15ECh. 3 - Prob. 16ECh. 3 - Prob. 17ECh. 3 - Prob. 18ECh. 3 - Prob. 19ECh. 3 - Prob. 20ECh. 3 - Prob. 3SRCh. 3 - Prob. 21ECh. 3 - Prob. 22ECh. 3 - Prob. 4SRCh. 3 - Prob. 23ECh. 3 - Prob. 24ECh. 3 - Prob. 25ECh. 3 - Prob. 26ECh. 3 - Prob. 5.1SRCh. 3 - Prob. 5.2SRCh. 3 - Compute the geometric mean of the following...Ch. 3 - Prob. 28ECh. 3 - Listed below is the percent increase in sales for...Ch. 3 - Prob. 30ECh. 3 - Prob. 31ECh. 3 - Prob. 32ECh. 3 - Prob. 33ECh. 3 - Prob. 34ECh. 3 - Prob. 6SRCh. 3 - Prob. 35ECh. 3 - Prob. 36ECh. 3 - Prob. 37ECh. 3 - Prob. 38ECh. 3 - Prob. 39ECh. 3 - Prob. 40ECh. 3 - Prob. 7SRCh. 3 - Prob. 41ECh. 3 - Prob. 42ECh. 3 - Prob. 43ECh. 3 - Prob. 44ECh. 3 - Plywood Inc. reported these returns on stockholder...Ch. 3 - Prob. 46ECh. 3 - Prob. 8SRCh. 3 - Prob. 47ECh. 3 - Prob. 48ECh. 3 - Prob. 49ECh. 3 - Prob. 50ECh. 3 - Prob. 51ECh. 3 - Prob. 52ECh. 3 - Prob. 9SRCh. 3 - Prob. 53ECh. 3 - The mean income of a group of sample observations...Ch. 3 - Prob. 55ECh. 3 - Prob. 56ECh. 3 - Prob. 10SRCh. 3 - Prob. 57ECh. 3 - Prob. 58ECh. 3 - Prob. 59ECh. 3 - Prob. 60ECh. 3 - The IRS was interested in the number of individual...Ch. 3 - Prob. 62ECh. 3 - Prob. 63CECh. 3 - Prob. 64CECh. 3 - Prob. 65CECh. 3 - Prob. 66CECh. 3 - Prob. 67CECh. 3 - Prob. 68CECh. 3 - Prob. 69CECh. 3 - Prob. 70CECh. 3 - Prob. 71CECh. 3 - Prob. 72CECh. 3 - Prob. 73CECh. 3 - A recent article suggested that, if you earn...Ch. 3 - Prob. 75CECh. 3 - Prob. 76CECh. 3 - Prob. 77CECh. 3 - Prob. 78CECh. 3 - The Apollo space program lasted from 1967 until...Ch. 3 - Prob. 80CECh. 3 - Prob. 81CECh. 3 - Prob. 82CECh. 3 - Prob. 83CECh. 3 - Prob. 84CECh. 3 - Bidwell Electronics Inc. recently surveyed a...Ch. 3 - Refer to the North Valley Real Estate data and...Ch. 3 - Prob. 87DACh. 3 - Refer to the Lincolnville School District bus...
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- 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? swarrow_forward11. 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_forward
- 9. 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_forward29 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_forward
- 27 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_forward30 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_forward
- 6. 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_forward4. 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_forward
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