// Numbas version: exam_results_page_options {"name": "Week 7 Quiz", "metadata": {"description": "", "licence": "None specified"}, "duration": 0, "percentPass": 0, "showQuestionGroupNames": false, "shuffleQuestionGroups": false, "showstudentname": true, "question_groups": [{"name": "Group", "pickingStrategy": "all-shuffled", "pickQuestions": 1, "questionNames": ["", "", "", "", "", "", "", "", ""], "variable_overrides": [[], [], [], [], [], [], [], [], []], "questions": [{"name": "Accessibility and Commnication", "extensions": [], "custom_part_types": [], "resources": [], "navigation": {"allowregen": true, "showfrontpage": false, "preventleave": false, "typeendtoleave": false}, "contributors": [{"name": "adam bretherton", "profile_url": "https://numbas.mathcentre.ac.uk/accounts/profile/18177/"}], "tags": [], "metadata": {"description": "", "licence": "None specified"}, "statement": "

Does accessibility imply communication?

", "advice": "

Communication requires accessibility in both directions

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Which of the following are required for an Ergodic Markov chain?

", "advice": "

An Ergodic Markov chain is aperiodic (period = 1) and irreducible (Only one communicating class)

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Which of the following states can a finite Markov chain have?

", "advice": "

All recurrent states in a finite Markov chain will be positive recurrent, since the expected number of steps to return to a recurrent state in a finite Markov chain is finite.

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Identify the classes for the Markov chain with the following transitional probability matrix:

\n

$\\mathbf{P}= \\begin{bmatrix}\\var{a1} & \\var{a2} & \\var{a3} & \\var{a4} & \\var{a5} \\\\ \\var{b1} & \\var{b2} & \\var{b3} & \\var{b4} & \\var{b5} \\\\ \\var{c1} & \\var{c2} & \\var{c3} & \\var{c4} & \\var{c5} \\\\ \\var{d1} & \\var{d2} & \\var{d3} & \\var{d4} & \\var{d5} \\\\ \\var{e1} & \\var{e2} & \\var{e3} & \\var{e4} & \\var{e5} \\\\ \\end{bmatrix} $

", "advice": "

Periodicity is determined by the GCD of steps taken to return to the state.

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"Ungrouped variables", "definition": "switch(\n Dec=1, 1-a1-a2-a3-a4,\n Dec=2, 0,\n Dec=3, 0)", "description": "", "templateType": "anything", "can_override": false}, "b1": {"name": "b1", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 1/random(3..6),\n Dec=3, 1/random(3..6))", "description": "", "templateType": "anything", "can_override": false}, "b2": {"name": "b2", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 0,\n Dec=3, 1/random(3..6))", "description": "", "templateType": "anything", "can_override": false}, "b3": {"name": "b3", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 1 -b1 -b2,\n Dec=3, 1 -b1 -b2)", "description": "", "templateType": "anything", "can_override": false}, "b4": {"name": "b4", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 0,\n Dec=3, 0)", "description": "", "templateType": "anything", "can_override": false}, "b5": {"name": "b5", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1-b1-b2-b3-b4,\n Dec=2, 0,\n Dec=3, 0)", "description": "", "templateType": "anything", "can_override": false}, "c1": {"name": "c1", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 1/random(3..6),\n Dec=3, 1/random(3..6))", "description": "", "templateType": "anything", "can_override": false}, "c2": {"name": "c2", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 1-c1-c3,\n Dec=3, 1-c1-c3)", "description": "", "templateType": "anything", "can_override": false}, "c3": {"name": "c3", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 0,\n Dec=3, 1/random(3..6))", "description": "", "templateType": "anything", "can_override": false}, "c4": {"name": "c4", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 0,\n Dec=3, 0)", "description": "", "templateType": "anything", "can_override": false}, "d1": {"name": "d1", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 0,\n Dec=3, 0)", "description": "", "templateType": "anything", "can_override": false}, "d2": {"name": "d2", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 0,\n Dec=3, 0)", "description": "", "templateType": "anything", "can_override": false}, "d3": {"name": "d3", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 1/2,\n Dec=3, 0)", "description": "", "templateType": "anything", "can_override": false}, "d4": {"name": "d4", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 1/random(3,4),\n Dec=3, 0)", "description": "", "templateType": "anything", "can_override": false}, "d5": {"name": "d5", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1-d1-d2-d3-d4,\n Dec=2, 1-d3-d4,\n Dec=3, 1)", "description": "", "templateType": "anything", "can_override": false}, "e1": {"name": "e1", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 0,\n Dec=3, 0)", "description": "", "templateType": "anything", "can_override": false}, "e2": {"name": "e2", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 0,\n Dec=3, 0)", "description": "", "templateType": "anything", "can_override": false}, "e3": {"name": "e3", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 0,\n Dec=3, 0)", "description": "", "templateType": "anything", "can_override": false}, "e4": {"name": "e4", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1/random(5..10),\n Dec=2, 1/random(2,3),\n Dec=3, 1)", "description": "", "templateType": "anything", "can_override": false}, "e5": {"name": "e5", "group": "Ungrouped variables", "definition": "switch(\n Dec=1, 1-e1-e2-e3-e4,\n Dec=2, 1-e4,\n Dec=3, 0)", "description": "", "templateType": "anything", "can_override": false}, "Dec": {"name": "Dec", "group": "Ungrouped variables", "definition": "random(1 .. 3#1)", "description": "

Chooses from the 3 answers.

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An irreducible periodic Markov chain will not have a limiting distribution?

", "advice": "

While this will have a unique stationary distribution, the periodicity will destroy the existence of a limiting distribution.

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A Markov chain must be Ergodic for the limiting distribution to exist and to have a unique stationary distribution?

", "advice": "

It is possible to have a Markov chain that has a unique stationary and limiting distribution and is NOT Ergodic.

\n

An example is a finite Markov chain that has 1 recurrent aperiodic class, and 1 or more transient classes.

\n

Such a Markov chain is not irreducible as it has more than 1 class (so not Ergodic), but it still will have a unique stationary and limiting distribution.

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Do the following Markov chains have a unique stationary distribution?

", "advice": "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
$0$$1$$0$$0$
$0$$0$$1$$0$
$0$$0$$0$$1$
$1$$0$$0$$0$
\n

Will have a unqiue stationary distribution $\\pi^T = [0.25, 0.25, 0.25, 0.25]$

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
$0$$1$$0$$0$
$1$$0$$0$$0$
$0$$0$$0.5$$0.5$
$0$$0$$0.5$$0.5$
\n

Will not have a unique stationary distribution two examples are $\\pi^T = [0.5, 0.5, 0, 0]$ and $\\pi^T = [0, 0, 0.5, 0.5]$

", "rulesets": {}, "builtin_constants": {"e": true, "pi,\u03c0": true, "i": true}, "constants": [], "variables": {}, "variablesTest": {"condition": "", "maxRuns": 100}, "ungrouped_variables": [], "variable_groups": [], "functions": {}, "preamble": {"js": "", "css": ""}, "parts": [{"type": "1_n_2", "useCustomName": false, "customName": "", "marks": 0, "scripts": {"mark": {"script": "// Reveal answers, score and advice\nthis.display.revealAnswer();\nthis.display.showScore();\nNumbas.controls.getAdvice();", "order": "before"}}, "customMarkingAlgorithm": "", "extendBaseMarkingAlgorithm": true, "unitTests": [], "showCorrectAnswer": true, "showFeedbackIcon": true, "variableReplacements": [], "variableReplacementStrategy": "originalfirst", "nextParts": [], "suggestGoingBack": false, "adaptiveMarkingPenalty": 0, "exploreObjective": null, "prompt": "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
$0$$1$$0$$0$
$0$$0$$1$$0$
$0$$0$$0$$1$
$1$$0$$0$$0$
", "minMarks": 0, "maxMarks": 0, "shuffleChoices": true, "displayType": "radiogroup", "displayColumns": 0, "showCellAnswerState": true, "choices": ["True", "False"], "matrix": ["1", "0"], "distractors": ["", ""]}, {"type": "1_n_2", "useCustomName": false, "customName": "", "marks": 0, "scripts": {"mark": {"script": "// Reveal answers, score and advice\nthis.display.revealAnswer();\nthis.display.showScore();\nNumbas.controls.getAdvice();", "order": "before"}}, "customMarkingAlgorithm": "", "extendBaseMarkingAlgorithm": true, "unitTests": [], "showCorrectAnswer": true, "showFeedbackIcon": true, "variableReplacements": [], "variableReplacementStrategy": "originalfirst", "nextParts": [], "suggestGoingBack": false, "adaptiveMarkingPenalty": 0, "exploreObjective": null, "prompt": "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
$0$$1$$0$$0$
$1$$0$$0$$0$
$0$$0$$0.5$$0.5$
$0$$0$$0.5$$0.5$
", "minMarks": 0, "maxMarks": 0, "shuffleChoices": true, "displayType": "radiogroup", "displayColumns": 0, "showCellAnswerState": true, "choices": ["True", "False"], "matrix": [0, "1"], "distractors": ["", ""]}], "partsMode": "all", "maxMarks": 0, "objectives": [], "penalties": [], "objectiveVisibility": "always", "penaltyVisibility": "always"}, {"name": "Stationary distribution requirements", "extensions": [], "custom_part_types": [], "resources": [], "navigation": {"allowregen": true, "showfrontpage": false, "preventleave": false, "typeendtoleave": false}, "contributors": [{"name": "adam bretherton", "profile_url": "https://numbas.mathcentre.ac.uk/accounts/profile/18177/"}], "tags": [], "metadata": {"description": "", "licence": "None specified"}, "statement": "

Which of the following are a requirement for a unique stationary distribution to exist?

", "advice": "

A unique stationary distribution will exist so long as there is only one positive recurrent class.

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Which of the following Markov chains has a limiting distribution?

", "advice": "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
$0$$1$$0$$0$
$0$$0$$1$$0$
$0$$0$$0$$1$
$1$$0$$0$$0$
\n

Will not have a limiting distribution as it is periodic.

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
$0$$1$$0$$0$
$1$$0$$0$$0$
$0$$0$$0.5$$0.5$
$0$$0$$0.5$$0.5$
\n

Will not have a unique stationary distribution and so will not have a limiting distribution.

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
$0.5$$0.5$$0$$0$
$0$$0.5$$0.5$$0$
$0$$0$$0.5$$0.5$
$0.5$$0$$0$$0.5$
\n

Will have a limiting distribution $\\pi^T = [0.25, 0.25, 0.25, 0.25]$.

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$0$$1$$0$$0$
$0$$0$$1$$0$
$0$$0$$0$$1$
$1$$0$$0$$0$
", "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
$0$$1$$0$$0$
$1$$0$$0$$0$
$0$$0$$0.5$$0.5$
$0$$0$$0.5$$0.5$
", "\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
$0.5$$0.5$$0$$0$
$0$$0.5$$0.5$$0$
$0$$0$$0.5$$0.5$
$0.5$$0$$0$$0.5$
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