Podcast
Questions and Answers
What is the time complexity of the function has_dominator in the worst-case scenario?
What is the time complexity of the function has_dominator in the worst-case scenario?
Which inequality best describes the behavior of the function 𝑓(𝑛) = 𝑛^4 with respect to 𝑔(𝑛) = 2^𝑛 in big-omega notation?
Which inequality best describes the behavior of the function 𝑓(𝑛) = 𝑛^4 with respect to 𝑔(𝑛) = 2^𝑛 in big-omega notation?
In the function has_dominator, what condition is being checked within the nested loops?
In the function has_dominator, what condition is being checked within the nested loops?
For a natural number 𝑚 > 1, what can be concluded about the prime number 𝑝 in relation to the expression (𝑚! + 2) ≤ 𝑝 ≤ (𝑚! + 𝑚)?
For a natural number 𝑚 > 1, what can be concluded about the prime number 𝑝 in relation to the expression (𝑚! + 2) ≤ 𝑝 ≤ (𝑚! + 𝑚)?
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Which of the following statements correctly describes the summation formula provided in the content?
Which of the following statements correctly describes the summation formula provided in the content?
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Given that (𝑛 + 1)^4 = 𝑛^4 + 4𝑛^3 + 6𝑛^2 + 4𝑛 + 1, what mathematical property does this equation illustrate?
Given that (𝑛 + 1)^4 = 𝑛^4 + 4𝑛^3 + 6𝑛^2 + 4𝑛 + 1, what mathematical property does this equation illustrate?
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In the context of algorithm analysis, what does big-oh notation represent?
In the context of algorithm analysis, what does big-oh notation represent?
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Which of the following statements correctly reflects the natural number properties used in the context provided?
Which of the following statements correctly reflects the natural number properties used in the context provided?
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What is the binary representation of the decimal number 61?
What is the binary representation of the decimal number 61?
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What is the consequence of the inductive step being improperly handled in the proof?
What is the consequence of the inductive step being improperly handled in the proof?
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Which pair of predicates can correctly demonstrate the condition given in the statement? (∀𝑛 ∈ ℕ, 𝑃(𝑛) ⇒ 𝑄(𝑛)) ⇒ (∃𝑚 ∈ ℕ, 𝑃(𝑚) ∧ 𝑄(𝑚))
Which pair of predicates can correctly demonstrate the condition given in the statement? (∀𝑛 ∈ ℕ, 𝑃(𝑛) ⇒ 𝑄(𝑛)) ⇒ (∃𝑚 ∈ ℕ, 𝑃(𝑚) ∧ 𝑄(𝑚))
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In the proof by induction, how is the base case verified for P(1)?
In the proof by induction, how is the base case verified for P(1)?
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For a complete bipartite graph G = (V, E), what can be inferred if |V1| = ⌊|V|/2⌋?
For a complete bipartite graph G = (V, E), what can be inferred if |V1| = ⌊|V|/2⌋?
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Why is P stated as connected in the context of graph theory?
Why is P stated as connected in the context of graph theory?
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What is a necessary condition for a graph G to be considered connected when |E| = |V| - 1?
What is a necessary condition for a graph G to be considered connected when |E| = |V| - 1?
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What will be the formula for 𝑖(𝑠), representing the value of 𝑖 after 𝑠 iterations in the doubler function?
What will be the formula for 𝑖(𝑠), representing the value of 𝑖 after 𝑠 iterations in the doubler function?
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What role does the assumption P(n) play during the proof process?
What role does the assumption P(n) play during the proof process?
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What is the correct general formula for the number of iterations of the loop in the doubler function for an input 𝑛?
What is the correct general formula for the number of iterations of the loop in the doubler function for an input 𝑛?
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Which of the following statements correctly expresses that there is exactly one dog that has fleas and lives in the arctic using the defined predicates?
Which of the following statements correctly expresses that there is exactly one dog that has fleas and lives in the arctic using the defined predicates?
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In proving that path P is connected, what must be shown explicitly?
In proving that path P is connected, what must be shown explicitly?
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In the context of the proof, what does it imply when a complete bipartite graph contains two partitions?
In the context of the proof, what does it imply when a complete bipartite graph contains two partitions?
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Study Notes
Question 1: Short Answer
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Part (a): Binary Representation of 61: The binary representation of 61 is 111101.
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Part (b): Predicates P(n) and Q(n): Define predicates to make (∀𝑛 ∈ ℕ, 𝑃(𝑛) ⇒ 𝑄(𝑛)) ⇒ (∃𝑚 ∈ ℕ, 𝑃(𝑚) ∧ 𝑄(𝑚)) true and (∃𝑛 ∈ ℕ, 𝑃(𝑛) ⇒ 𝑄(𝑛)) ⇒ (∀𝑚 ∈ ℕ, 𝑃(𝑚) ∧ 𝑄(𝑚)) false. One possible solution involves creating conditions where the implication is always true in the first statement but only true for some n in the second.
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Part (c): Moduli: The number 𝑖 that satisfies 𝑖 ≡ 2 (mod 3) and 𝑖 ≡ 4 (mod 5) is 14.
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Part (d): doubler(17) Loop Iterations: The loop in
doubler(17)
iterates 3 times. -
Part (e): Formula for i(s): The formula for 𝑖(𝑠), the value of 𝑖 after 𝑠 iterations of the
doubler
loop, is 𝑖(𝑠) = 2s. -
Part (f): Iterations for doubler(n): The number of iterations for
doubler(n)
is ⌈log2(√𝑛)⌉. -
Part (g): Predicate Logic Statement for Dogs: The statement "There is exactly one dog that has fleas and lives in the arctic" can be expressed as: ∃𝑑 ∈ 𝐷, (𝐴(𝑑) ∧ 𝐹(𝑑)) ∧ (∀𝑑′ ∈ 𝐷, (𝐴(𝑑′) ∧ 𝐹(𝑑′)) ⇒ 𝑑 = 𝑑′).
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Part (h): Units Digit of 398312: The units digit of 398312 is 1.
Question 2: Number Theory
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Part (a): Moduli Proof: To prove that if 𝑎 ≡ 𝑏 (mod 17) and 𝑎 ≡ 𝑏 (mod 19), then 𝑎 ≡ 𝑏 (mod 17 × 19), utilize the given theorem about prime factorization and the properties of modular arithmetic. Since 17 and 19 are prime, if they both divide (a-b), then their product (17*19) must also divide (a-b).
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Part (b): Prime-Free Range: Prove that there is no prime number 𝑝 such that (𝑚!+ 2) ≤ 𝑝 ≤ (𝑚!+ 𝑚) for natural number 𝑚 > 1. All integers within that range are composite because they are divisible by integers from 2 to m..
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Part (c): Faulty Proof Analysis: The inductive proof for P(n): "∀𝐺 = (𝑉 , 𝐸), |𝐸| = |𝑉 | − 1 ⇒ 𝐺 is connected" breaks down at n=3. A graph with 3 vertices and 2 edges might not be connected, showing the inductive step is flawed for this specific case.
Question 3: Big-Omega/Big-Oh
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Part (a): Proof that f ∉ Ω(g): Prove that 𝑛4 ∉ Ω(2𝑛) by showing that no constants cΩ and nΩ exist to satisfy the definition of big-Omega for all n ≥ nΩ.
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Part (b): Proof that f ∈ 𝑂(g): Prove that 𝑛4 ∈ 𝑂(2𝑛) by finding constants c𝑂 and n𝑂 that satisfy the Big-Oh definition for all n ≥ n𝑂.
Question 4: Runtime Analysis
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Part (a): Upper Bound for has_dominator: The worst-case runtime for
has_dominator
is 𝑂(𝑛2). This is because of its nested loops, leading to roughly n(n-1)/2 comparisons in the worst case, which is of the order of n². A formal proof would involve showing that the number of operations is bounded above by a quadratic function of n for all sufficiently large n.
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