Discrete Mathematics: Introduction to Mathematical Reasoning
1st Edition
ISBN: 9780495826170
Author: Susanna S. Epp
Publisher: Cengage Learning
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Chapter 2.3, Problem 2ES
To determine
To provide a minor premise to the argument based on the Major premise, conclusion and the fact that Modus Ponens/ Modus Tollens is applicable.
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Students have asked these similar questions
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.
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
3
2,3,
ample
and
rical
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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?
Chapter 2 Solutions
Discrete Mathematics: Introduction to Mathematical Reasoning
Ch. 2.1 - Prob. 1ESCh. 2.1 - Prob. 2ESCh. 2.1 - Prob. 3ESCh. 2.1 - Prob. 4ESCh. 2.1 - Prob. 5ESCh. 2.1 - Prob. 6ESCh. 2.1 - Prob. 7ESCh. 2.1 - Prob. 8ESCh. 2.1 - Prob. 9ESCh. 2.1 - Prob. 10ES
Ch. 2.1 - Prob. 11ESCh. 2.1 - Prob. 12ESCh. 2.1 - Prob. 13ESCh. 2.1 - Prob. 14ESCh. 2.1 - Prob. 15ESCh. 2.1 - Prob. 16ESCh. 2.1 - Prob. 17ESCh. 2.1 - Prob. 18ESCh. 2.1 - Prob. 19ESCh. 2.1 - Prob. 20ESCh. 2.1 - Prob. 21ESCh. 2.1 - Prob. 22ESCh. 2.1 - Prob. 23ESCh. 2.1 - Prob. 24ESCh. 2.1 - Prob. 25ESCh. 2.1 - Prob. 26ESCh. 2.1 - Prob. 27ESCh. 2.1 - Prob. 28ESCh. 2.1 - Prob. 29ESCh. 2.1 - Prob. 30ESCh. 2.1 - Prob. 31ESCh. 2.1 - Prob. 32ESCh. 2.1 - Prob. 33ESCh. 2.1 - Prob. 34ESCh. 2.1 - Prob. 35ESCh. 2.1 - Prob. 36ESCh. 2.1 - Prob. 37ESCh. 2.1 - Prob. 38ESCh. 2.1 - Prob. 39ESCh. 2.1 - Prob. 40ESCh. 2.1 - Prob. 41ESCh. 2.1 - Prob. 42ESCh. 2.1 - Prob. 43ESCh. 2.1 - Prob. 44ESCh. 2.1 - Prob. 45ESCh. 2.1 - Prob. 46ESCh. 2.1 - Prob. 47ESCh. 2.2 - Prob. 1ESCh. 2.2 - Prob. 2ESCh. 2.2 - Prob. 3ESCh. 2.2 - Prob. 4ESCh. 2.2 - Prob. 5ESCh. 2.2 - Prob. 6ESCh. 2.2 - Prob. 7ESCh. 2.2 - Prob. 8ESCh. 2.2 - Prob. 9ESCh. 2.2 - Prob. 10ESCh. 2.2 - Prob. 11ESCh. 2.2 - Prob. 12ESCh. 2.2 - Prob. 13ESCh. 2.2 - Prob. 14ESCh. 2.2 - Prob. 15ESCh. 2.2 - Prob. 16ESCh. 2.2 - Prob. 17ESCh. 2.2 - Prob. 18ESCh. 2.2 - Prob. 19ESCh. 2.2 - Prob. 20ESCh. 2.2 - Prob. 21ESCh. 2.2 - Prob. 22ESCh. 2.2 - Prob. 23ESCh. 2.2 - Prob. 24ESCh. 2.2 - Prob. 25ESCh. 2.2 - Prob. 26ESCh. 2.2 - Prob. 27ESCh. 2.2 - Prob. 28ESCh. 2.2 - Prob. 29ESCh. 2.2 - Prob. 30ESCh. 2.2 - Prob. 31ESCh. 2.2 - Prob. 32ESCh. 2.2 - Prob. 33ESCh. 2.2 - Prob. 34ESCh. 2.2 - Prob. 35ESCh. 2.2 - Prob. 36ESCh. 2.2 - Prob. 37ESCh. 2.2 - Prob. 38ESCh. 2.2 - Prob. 39ESCh. 2.2 - Prob. 40ESCh. 2.2 - Prob. 41ESCh. 2.2 - Prob. 42ESCh. 2.2 - Prob. 43ESCh. 2.2 - Prob. 44ESCh. 2.2 - Prob. 45ESCh. 2.2 - Prob. 46ESCh. 2.3 - Prob. 1ESCh. 2.3 - Prob. 2ESCh. 2.3 - Prob. 3ESCh. 2.3 - Prob. 4ESCh. 2.3 - Prob. 5ESCh. 2.3 - Prob. 6ESCh. 2.3 - Prob. 7ESCh. 2.3 - Prob. 8ESCh. 2.3 - Prob. 9ESCh. 2.3 - Prob. 10ESCh. 2.3 - Prob. 11ESCh. 2.3 - Prob. 12ESCh. 2.3 - Prob. 13ESCh. 2.3 - Prob. 14ESCh. 2.3 - Prob. 15ESCh. 2.3 - Prob. 16ESCh. 2.3 - Prob. 17ESCh. 2.3 - Prob. 18ESCh. 2.3 - Prob. 19ESCh. 2.3 - Prob. 20ESCh. 2.3 - Prob. 21ESCh. 2.3 - Prob. 22ESCh. 2.3 - Prob. 23ESCh. 2.3 - Prob. 24ESCh. 2.3 - Prob. 25ESCh. 2.3 - Prob. 26ESCh. 2.3 - Prob. 27ESCh. 2.3 - Prob. 28ESCh. 2.3 - Prob. 29ESCh. 2.3 - Prob. 30ESCh. 2.3 - Prob. 31ESCh. 2.3 - Prob. 32ESCh. 2.3 - Prob. 33ESCh. 2.3 - Prob. 34ESCh. 2.3 - Prob. 35ESCh. 2.3 - Prob. 36ESCh. 2.3 - Prob. 37ESCh. 2.3 - Prob. 38ESCh. 2.3 - Prob. 39ESCh. 2.3 - Prob. 40ESCh. 2.3 - Prob. 41ESCh. 2.3 - Prob. 42ESCh. 2.3 - Prob. 43ESCh. 2.3 - Prob. 44ES
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- 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
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- 2. Derive the component transformation equations for tensors shown be- low where [C] = [BA] is the direction cosine matrix from frame A to B. B[T] = [C]^[T][C]T 3. The transport theorem for vectors shows that the time derivative can be constructed from two parts: the first is an explicit frame-dependent change of the vector whereas the second is an active rotational change of the vector. The same holds true for tensors. Starting from the previous result, derive a version of transport theorem for tensors. [C] (^[T])[C] = dt d B dt B [T] + [WB/A]B[T] – TWB/A] (10 pt) (7pt)arrow_forwardUse the graph of the function y = f (x) to find the value, if possible. f(x) 8 7 6 Q5 y 3 2 1 x -8 -7 -6 -5 -4 -3 -2 -1 1 2 3 4 5 6 7 8 -1 -2 -3 -4 -5 -6 -7 -8+ Olim f(z) x-1+ O Limit does not exist.arrow_forward3. Prove that, for any random variable X, the minimum of E(X - a)² is attained for a = EX. Provedarrow_forward
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