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Last time we talked about propositional logic, a logic on simple statements.
This time we will talk about first order logic, a logic on quantified statements.
First order logic is much more expressive than propositional logic.
The topics on first order logic are:
1-Quantifiers
2-Negation
3-Multiple quantifiers
4-Arguments of quantified statements
Math 235 - Summer 2015Homework 2Due Monday June 8 in cla.docxandreecapon
Math 235 - Summer 2015
Homework 2
Due Monday June 8 in class
Remember: In this course, you must always show reasoning for your answers. You can use any result we have
proved in class, in textbook reading, or in a previous homework.
Problem 1 For each of the following problems, you must justify your answer by finding the general solution
to the corresponding system of linear equations, or by showing that no solution exists.
(a) In the vector space P3(R), can −2x3 − 11x2 + 3x+ 2 be written as a linear combination of vectors in
{x3 − 2x2 + 3x− 1, 2x3 + x2 + 3x− 2}?
(b) In the vector space M2×2(R), can
(
1 0
0 1
)
be written as a linear combination of vectors
in
{(
1 0
−1 0
)
,
(
0 1
0 1
)
,
(
1 1
0 0
)}
?
Problem 2 Show that a subset W of a vector space V (over a field F ) is a subspace of V if and only if
span(W ) = W .
Problem 3 You are given a subset S of a vector space V . Determine whether S is linearly dependent or
linearly independent using exclusively methods developed in this course, and justify your answers.
(a) V = R3 and S = {(1, 2,−1), (2,−3, 1), (2, 3,−5)}.
(b) V = P3(R) and S = {1, 1 + 2t+ t2, 1− 2t+ t3, t2 + t3}.
(c) V = F(R,R) and S = {t, et, sin(t)}.
Problem 4 Prove that a subset S of a vector space V is linearly dependent if and only if there exists a
proper subset S′ ( S with the same span as S.
Problem 5 Exercise 1.6.13 from the textbook.
Problem 6 You are given a subspace S of M2×2(F ), the vector space of 2 × 2 matrices with entries in a
field F . You are required to find a basis for this subspace, and to find the dimension of this subspace.
For each problem, you DO NOT need to prove that S is a subspace, but you DO need to prove that your
conjectured basis is, in fact, a basis (that is, you need to show it is a linearly independent generating set for
S).
(a) S is the subspace of all diagonal 2× 2 matrices with entries in F .
(b) S is the subspace of all symmetric 2× 2 matrices with entries in F .
(c) S is the subspace of all skew-symmetric 2× 2 matrices with entries in F .
Problem 7 Let W1 and W2 be subspaces of a finite-dimensional vector space V . Prove that dim(W1∩W2) ≤
min{dim(W1),dim(W2)} and dim(W1 +W2) ≥ max{dim(W1),dim(W2)}.
Problem 8 Each of the maps below goes from one vector space to another (where both vectors spaces are
over the same field). For each map: prove that it is linear, determine whether it is one-to-one or not (prove
your answer), and determine whether it is onto or not (prove your answer).
(a) T : P3(R)→M2×2(R) defined by T (p) =
(
p(0) p′(0)
p′′(0) p′′′(0)
)
.
(b) T : M2×2(F ) → F defined by T (A) = tr(A), where F is a field. (Recall that for an n × n matrix,
tr(A) =
∑n
i=1Aii.)
1
(c) T : R2 → R3 defined by T ((a, b)) = (a, b, a+ b).
(Hint: You may find an analysis of rank and nullity useful here.)
Problem 9 Suppose that T : R2 → R2 is linear and that T ((1, 2)) = (3, 4) and T ((1, 3)) = (0, 1). Find
T ((1, 0)). Is T one-to-one? Justify your answer.
Problem 10 Let ...
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Last time we talked about propositional logic, a logic on simple statements.
This time we will talk about first order logic, a logic on quantified statements.
First order logic is much more expressive than propositional logic.
The topics on first order logic are:
1-Quantifiers
2-Negation
3-Multiple quantifiers
4-Arguments of quantified statements
Math 235 - Summer 2015Homework 2Due Monday June 8 in cla.docxandreecapon
Math 235 - Summer 2015
Homework 2
Due Monday June 8 in class
Remember: In this course, you must always show reasoning for your answers. You can use any result we have
proved in class, in textbook reading, or in a previous homework.
Problem 1 For each of the following problems, you must justify your answer by finding the general solution
to the corresponding system of linear equations, or by showing that no solution exists.
(a) In the vector space P3(R), can −2x3 − 11x2 + 3x+ 2 be written as a linear combination of vectors in
{x3 − 2x2 + 3x− 1, 2x3 + x2 + 3x− 2}?
(b) In the vector space M2×2(R), can
(
1 0
0 1
)
be written as a linear combination of vectors
in
{(
1 0
−1 0
)
,
(
0 1
0 1
)
,
(
1 1
0 0
)}
?
Problem 2 Show that a subset W of a vector space V (over a field F ) is a subspace of V if and only if
span(W ) = W .
Problem 3 You are given a subset S of a vector space V . Determine whether S is linearly dependent or
linearly independent using exclusively methods developed in this course, and justify your answers.
(a) V = R3 and S = {(1, 2,−1), (2,−3, 1), (2, 3,−5)}.
(b) V = P3(R) and S = {1, 1 + 2t+ t2, 1− 2t+ t3, t2 + t3}.
(c) V = F(R,R) and S = {t, et, sin(t)}.
Problem 4 Prove that a subset S of a vector space V is linearly dependent if and only if there exists a
proper subset S′ ( S with the same span as S.
Problem 5 Exercise 1.6.13 from the textbook.
Problem 6 You are given a subspace S of M2×2(F ), the vector space of 2 × 2 matrices with entries in a
field F . You are required to find a basis for this subspace, and to find the dimension of this subspace.
For each problem, you DO NOT need to prove that S is a subspace, but you DO need to prove that your
conjectured basis is, in fact, a basis (that is, you need to show it is a linearly independent generating set for
S).
(a) S is the subspace of all diagonal 2× 2 matrices with entries in F .
(b) S is the subspace of all symmetric 2× 2 matrices with entries in F .
(c) S is the subspace of all skew-symmetric 2× 2 matrices with entries in F .
Problem 7 Let W1 and W2 be subspaces of a finite-dimensional vector space V . Prove that dim(W1∩W2) ≤
min{dim(W1),dim(W2)} and dim(W1 +W2) ≥ max{dim(W1),dim(W2)}.
Problem 8 Each of the maps below goes from one vector space to another (where both vectors spaces are
over the same field). For each map: prove that it is linear, determine whether it is one-to-one or not (prove
your answer), and determine whether it is onto or not (prove your answer).
(a) T : P3(R)→M2×2(R) defined by T (p) =
(
p(0) p′(0)
p′′(0) p′′′(0)
)
.
(b) T : M2×2(F ) → F defined by T (A) = tr(A), where F is a field. (Recall that for an n × n matrix,
tr(A) =
∑n
i=1Aii.)
1
(c) T : R2 → R3 defined by T ((a, b)) = (a, b, a+ b).
(Hint: You may find an analysis of rank and nullity useful here.)
Problem 9 Suppose that T : R2 → R2 is linear and that T ((1, 2)) = (3, 4) and T ((1, 3)) = (0, 1). Find
T ((1, 0)). Is T one-to-one? Justify your answer.
Problem 10 Let ...
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A set of notes prepared for an introductory machine learning course, assuming very limited linear algebra background, because all linear algebra operations are fully written out. These notes go into thorough derivations of the generalized linear regression formulation, demonstrating how to write it out in matrix form.
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A set of notes prepared for an introductory machine learning course, assuming very limited linear algebra background, because all linear algebra operations are fully written out. These notes go into thorough derivations of the generalized linear regression formulation, demonstrating how to write it out in matrix form.
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Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
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Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
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A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
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1. Discrete Stochastic
Processes
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2. Circle the name of your Tutorial Instructor:
Ashish Carole Christos Eric
George Jack Nick Tina
• This quiz is closed book. There is an Appendix giving the definitions of standard
properties of relations.
• There are four (4) problems totaling 100 points. Problems are labeled with their point
values.
• Put your name on the top of every page – these pages may be separated for grading.
• Write your solutions in the space provided. If you need more space, write on the back
of the sheet containing the problem. Please keep your entire answer to a problem on
that problem’s page.
• You may assume any of the results presented in class or in the lecture notes.
• Be neat and write legibly. You will be graded not only on the correctness of your
answer, but also on the clarity with which you express it.
Problems
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3. Problem 1 Consider the following system specifications1.
1. The system is in multiuser state if it is operating normally.
2. If the system is operating normally, then the kernel is functioning.
3. The kernel is not functioning or the system is in interrupt mode.
4. If the system is not in multiuser state, then it is in interrupt mode.
5. The system is not in interrupt mode.
(a) To make sense of these confusing conditions, let’s introduce four Boolean variables.
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4. M ::= in Multiuser state (1)
N ::= operating Normally (2)
K ::= Kernel is functioning (3)
I ::= in Interrupt mode (4)
Translate the five statements in the specification into propositional
logic notation: ∧,∨,¬, −→
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5. (b) Are these system specifications consistent? . Prove it!
Problem 2
For each of the following logical formulas with domain of discourse the natural numbers,
N, indicate whether it is a possible formulation of I:
the Induction Axiom,
S: the Strong Induction Axiom,
L: the Least Number Principle (also known as Wellordering),
or N: None of these.
For example, the ordinary Induction Axiom could be expressed by the following formula, so
it gets labelled “I”.
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6. This is a multiple choice problem: do not explain your answer.
(a) (P(b) ∧ [∀k ≥ b P(k) −→ P(k + 1)]) −→ ∀k ≥ b P(k)
(b) (P(b) ∧ [∀k ≤ b P(k) −→ P(k + 1)]) −→ ∀k ≤ b P(k)
(c) [∀b (∀k < b P(k)) −→ P(b)] −→ ∀k P(k) (
(d) (∃n P(n)) −→ ∃n ∀k < n P(k)
(e) ∀n [P(n) −→ (∃n P(n) ∧ ∀k < n P(k))]
Problem 3 Classify each of the following binary relations as
E: An equivalence relation.
T: A Total order,
P: A Partial order that is not total.
S: A Symmetric relation that is not transitive.
N: None of the above..
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7. This is a multiple choice problem: do not explain your answer.
(a) The relation xRy between times of day such that x and y are at most twenty minutes
apart.
(b) The relation xRy between times of day such that x is more than twenty minutes later
than y.
(c) The relation xRy over all words in this sentence such that x does not appear after y.
(Consider “x”, “y”, and “xRy” to be words.)
(d) The relation xRy over all words in this sentence such that word x does not appear
after word y.
(e) The relation xRy over all words in this sentence such that the final appearance of y
occurs after x.
Problem 4 To encourage collaborative study, the 6.042 staff is considering assigning
each student to a study group with two or three other students. Prove that as long as the
enrollment is large enough, the class can always be divided into such study groups.
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8. Appendix
A binary relation, R, on a set A is
• reflexive iff xRx,
• symmetric iff xRy −→ yRx,
• antisymmetric iff xRy ∧ yRx −→ x = y,
• transitive iff xRy ∧ yRz −→ xRz,
for all x, y, z ∈ A.
• R is an equivalence relation iff it is reflexive, symmetric and transitive.
• R is a partial order iff it is transitive and antisymmetric.
• R is a total order iff it is a partial order and for all x = y ∈ A either xRy or yRx.
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9. Problem 1 Consider the following system specifications1.
1. The system is in multiuser state iff it is operating normally.
2. If the system is operating normally, then the kernel is functioning.
3. The kernel is not functioning or the system is in interrupt mode.
4. If the system is not in multiuser state, then it is in interrupt mode.
5. The system is not in interrupt mode.
(a) To make sense of these confusing conditions, let’s introduce four Boolean
variables.
M ::= in Multiuser state (1)
N ::= operating Normally (2)
K ::= Kernel is functioning (3)
I ::= in Interrupt mode (4)
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10. Translate the five statements in the specification into propositional logic notation: ∧,∨,¬,
−→ ,←→
Solution.
M N ←→ (5)
N −→ K (6)
¬K ∨ I (7)
¬M −→ I (8)
¬I (9)
(b) (0 points) Are these system specifications consistent? . Prove it!
Solution. There are several ways to approach this problem. One is to construct a truth
table with sixteen lines—one for each way of assigning truth values to the four variables
M, N, K, and I.
We can avoid the cumbersome truthtable if we reason by cases. Case 1: I is true. Then
the last formula (9) is false, and the whole specification is false. Case 2: I is false. Now
formula (8) can be true only if ¬M is false, that is, only if M is true. Likewise, formula (7)
can be true only if ¬K is true, that is, K is false.
Since K is false, formula (6) can be true only if N is false. Thus, we have deduced that in
order to be consistent in this case, we must have
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11. I = false
M = true
K = false
N = false.
But now formula (5) is false, so it is impossible for all the formulas to be true: the system is
inconsistent.
Problem 2 For each of the following logical formulas with domain of discourse the
natural numbers, N, indicate whether it is a possible formulation of
I: the Induction Axiom,
S: the Strong Induction Axiom,
L: the Least Number Principle (also known as Wellordering), or
N: None of these.
For example, the ordinary Induction Axiom could be expressed by the following formula, so
it gets labelled “I”.
(P(0) ∧ [∀k P(k) −→ P(k + 1)]) −→ ∀k P(k) I
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12. This is a multiple choice problem: do not explain your answer.
(a) (P(b) ∧ [∀k ≥ b P(k) −→ P(k + 1)]) −→ ∀k ≥ b P(k)
Solution. I. This is a perfect formulation of the Induction Axiom. b is used for the base
case; P(k) −→ P(k + 1) is the inductive case.
(b) (P(b) ∧ [∀k ≤ b P(k) −→ P(k + 1)]) −→ ∀k ≤ b P(k) Solution. N. The two occurences
of k <= b should have been k >= b
(c) [∀b (∀k < b P(k)) −→ P(b)] −→ ∀k P(k) Solution. S. Since you are assuming P(k)
for all k < b, this is strong induction.
(d) (∃n P(n)) −→ ∃n ∀k < n P(k) Solution. N. This statement is in fact always true;
when n = 0, ∀k < n P(k). It should say P(n) ∧ ∀k < n; P(k)
(e) ∀n [P(n) −→ (∃n P(n) ∧ ∀k < n P(k))] Solution. L. This is a valid formulation; it does
not have that problem in (2d).
Problem 3 . Classify each of the following binary relations as
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13. E: An equivalence relation.
T: A Total order,
P: A Partial order that is not total
S: A Symmetric relation that is not transitive.
N: None of the above.
This is a multiple choice problem: do not explain your answer.
(a) The relation xRy between times of day such that x and y are at most twenty
minutes apart.
Solution. S: This relation is reflexive and symmetric. It is not transitive; Consider the
counterexample: 1:00R 1:15, 1:15R 1:22 but ¬1:00R 1:22.
(b) The relation xRy between times of day such that x is more than twenty minutes later
than y.
Solution. P: This relation is antisymmetric and transitive but not reflexive (since a time
isn’t 20 minutes after itself). This is not a total ordering because some times are
incomparable to each other. For example, 1:15 is incomparable to 1:22
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14. Note: This answer assumes that the question was referring to the moments in time in
a single day. Otherwise, one could argue that 1:00 precedes 1:22 on tuesday, but
1:22 on tuesday precedes 1:00 on wednesday, and then the relation would not be
antisymmetric.
(c) The relation xRy over all words in this sentence such that x does not appear after y.
(Consider “x”, “y”, and “xRy” to be words.)
Solution. T: Because all the words in the sentence are unique, this relation is transitive,
antisymmetric, and reflexive. This makes the relation a partial order. However, the
relation is also a total order, because any two elements are comparable.
(d) The relation xRy over all words in this sentence such that word x does not
appear after word y.
Solution. P: This is the same as saying that all appearances of a word x occur
before all appearances of a word y. While apparently very similar to part c, this
relation is not reflexive because the word word appears twice in the sentence. It is
transitive and antisymmetric, but not a total order because all the words between
the two occurrences of word are incomparable to word.
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15. (e) The relation xRy over all words in this sentence such that the final appearance of y
occurs after x.
Solution. N: This relation is not reflexive and transitive. It is neither symmetric nor
antisymmetric; the word the occurs twice, all the others once. All words w, between the
two occurrences of the satisfy wR the and theRw. So R is not antisymmetric. But “x” is
maximal, so it’s not symmetric either
Problem 4 (35 points). To encourage collaborative study, the 6.042 staff is
considering assigning each student to a study group with two or three other
students. Prove that as long as the enrollment is large enough, the class can
always be divided into such study groups.
Solution. Proof. The proof is by strong induction. The induction hypothesis is
that a class with n ≥ 6 students can be divided into teams of 3 or 4. More
precisely
P(n) ::= n ≥ 6 −→ ∃x, y ∈ N 3x + 4y = n.
For any n ≥ 0, we may assume P(6), . . . , P(n − 1) to prove P(n).
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16. Case 1: (n < 6). P(n) holds because the hypothesis n ≥ 6 is false.
Case 2: (n = 6, 7, or 8) P(6) is true because there could be two teams of 3, P(7) is
true because there could be a team of 3 and a team of 4, and P(8) is true because
there could be two teams of 4.
Case 3: (n ≥ 9). Of course n > n−3 so P(n−3) holds by the strong induction
hypothesis. But n − 3 ≥ 6, so P(n − 3) implies 3x + 4y= n − 3 for some x, y ∈ N,
and therefore 3x + 4y = n where x ::= x + 1 and y ::= y . So P(n) holds, as required.
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