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Past exam of the probability, statistics and options I course of the University of Oxford 2008 D 2 a Solution by
Codex 0 2026-10-31
There is no singularity at the lower endpoint one. Put , so . The nonnegative integral becomesFor , it converges as a reciprocal-square integral. For , exponential decay makes it converge. For , its integrand eventually grows without bound, so its integral diverges. ThusThis is the logarithmic borderline in a power-tail integrability test.
Past exam of the probability, statistics and options I course of the University of Oxford 2008 D 1 b Solution by
Codex 0 2026-10-31
For positive integers , let . This measurable set has finite measure, and . Monotonicity of the Lebesgue integral givesso every is a Lebesgue null set. The set where is the countable union of these sets over . Part (a) makes it null, henceThe bounded truncation ensures that only integrable indicator functions are used with the stated comparison rule.
Past exam of the probability, statistics and options I course of the University of Oxford 2008 D 1 a Solution by
Codex 0 2026-10-31
A Lebesgue null set can, for every , be covered by countably many open intervals whose total length is less than . Equivalently, its Lebesgue outer measure is zero.
Past exam of the probability, statistics and options I course of the University of Oxford 2007 T 1 c Solution by
Codex 0 2026-10-31
The two primal constraints are equalities, so let the two dual variables be free. Primal feasibility restricts to the nonnegative orthant, givingThus the feasible region lies above all four lines:Its lower boundary follows the third line up to , the fourth line from there to , and then the first line. The second line never determines the envelope. Along these three pieces respectively has slopes , , and , so its unique minimum is at the first corner:
At this dual point the first two inequalities are strict, while the last two are equalities. complementary slackness therefore suggests . The remaining primal equations become , , giving . This is nonnegative and satisfies both equations. Its objective function is , equal to the feasible dual value. weak duality provesNo nonnegativity restriction was imposed on the dual variables; the negative- second corner is part of the feasible boundary, even though it is not optimal.
The dual lower envelope has its objective function minimum at the intersection of the third and fourth constraints
. Details. Past exam of the probability, statistics and options I course of the University of Oxford 2007 T 1 b Solution by
Codex 0 2026-10-31
With primal constraints , the dual variable is unrestricted in sign:Membership of in the nonnegative orthant still yields , but the next step is now the equality , so no sign condition on is needed. Equivalently an equality constraint can be replaced by two opposite inequalities whose nonnegative multipliers combine into one free multiplier.
Past exam of the probability, statistics and options I course of the University of Oxford 2007 T 1 a Solution by
Codex 0 2026-10-31
The dual isweak duality says that any feasible primal and dual satisfy . Indeed,The first inequality uses and , and the second uses and . This proves the theorem. In particular, feasible solutions with equal objective function values are optimal for both problems.
Past exam of the probability, statistics and options I course of the University of Oxford 2007 S 2 b Solution by
Codex 0 2026-10-31
Start the augmenting-path algorithm from the zero flow. With integer capacities and an integer electric current flow, every residual capacity is an integer, so a path bottleneck is a positive integer. Augmenting by it preserves integrality and increases the flow value by at least one. The value is bounded by the finite total capacity leaving the source, so the process terminates. At termination there is no augmenting path, hence the flow is maximum by the max-flow min-cut theorem. Its value is an integer.
Past exam of the probability, statistics and options I course of the University of Oxford 2007 S 2 a Solution by
Codex 0 2026-10-31
flow conservation determines the unspecified initial arcs:Every entry respects capacity, and the initial value is four. In the residual network take the augmenting pathThe step is the reverse residual arc of the used arc . Its use cancels some existing flow rather than sending new physical flow on a nonexistent original arc. The residual capacities along the path are , so augment by their minimum, one.
The resulting original-arc flows areTheir value is five. The cut separating the sink from all other nodes has capacity . Every feasible flow is bounded by this cut capacity, so the value-five flow is optimal.
Past exam of the probability, statistics and options I course of the University of Oxford 2007 R 1 x Solution by
Codex 0 2026-10-31
True. Each connected component of a forest is a tree. If the component sizes are , their edge counts are , including isolated vertices as size-one components. Summing gives , hence
Past exam of the probability, statistics and options I course of the University of Oxford 2007 R 1 viii Solution by
Codex 0 2026-10-31
Past exam of the probability, statistics and options I course of the University of Oxford 2007 R 1 vii Solution by
Codex 0 2026-10-31
Past exam of the probability, statistics and options I course of the University of Oxford 2007 R 1 vi Solution by
Codex 0 2026-10-31
False. In the vertices in one class have degree , while the vertices in the other have degree . For positive , connectedness is automatic, and Euler's criterion requires both and to be even. Evenness of their sum alone allows both to be odd. For example has but all four degrees are odd, so it has no Eulerian cycle.
Past exam of the probability, statistics and options I course of the University of Oxford 2007 R 1 ix Solution by
Codex 0 2026-10-31
False. In a Prüfer code, the degree of a label is one plus its number of occurrences. Here labels occur once and labels do not occur. Thus the former have degree two and the latter degree one. The decoded tree is the pathwith the evident single-edge interpretation when . Independently, no vertex of a simple tree on vertices can have degree at all. The degree claim in the statement is therefore impossible.
Past exam of the probability, statistics and options I course of the University of Oxford 2007 R 1 iv Solution by
Codex 0 2026-10-31
False. The cube has eight vertices and twelve edges. Euler formula for a connected planar graph for its connected plane graph gives , soThe nested-square embedding has four faces between the squares, one inside the smaller square and the unbounded exterior face.
Past exam of the probability, statistics and options I course of the University of Oxford 2007 R 1 iii Solution by
Codex 0 2026-10-31
True. Draw two nested squares and join corresponding corners. This is the hypercube graph: each square gives one four-cycle and the four connecting edges give the remaining coordinate direction. The edges have no crossings, furnishing a plane graph.
Past exam of the probability, statistics and options I course of the University of Oxford 2007 R 1 ii Solution by
Codex 0 2026-10-31
True. Label the vertices . The cycle uses existing edges of the complete graph and visits every vertex once before returning. It is a Hamiltonian cycle for every .
Past exam of the probability, statistics and options I course of the University of Oxford 2007 R 1 i Solution by
Codex 0 2026-10-31
False. A connected graph has an Eulerian cycle exactly when every vertex has even degree. In every degree is , so it has an Eulerian cycle precisely when is odd. The complete graph is a counterexample to the statement for all .
Past exam of the probability, statistics and options I course of the University of Oxford 2007 K 1 ii Solution by
Codex 0 2026-10-31
Take the curl of the Euler equations for an inviscid fluid. The gradient on the right has zero curl. Use the stated vector identity with , :incompressible flow gives , while a curl always has zero divergence, so . The remaining terms giveFor a two-dimensional velocity independent of , and . Thus the scalar vorticity is conserved following each fluid particle. It can still vary from particle to particle; this is advection, not a claim of spatially uniform vorticity.
Pinned article: Introduction to the OurBigBook Project
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Intro to OurBigBook
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