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    "# Preview\n",
    "\n",
    "- Use these questions before class to check your familiarity with the chapter glossary and core terms.\n",
    "- Sign in from the account menu before you start answering the questions.\n",
    "- Multiple submissions are allowed. The highest score is kept.\n",
    "\n",
    "Review the [Chapter 13 glossary](../1300-multiple-regression.ipynb) before class. These ten questions mix multiple-choice and true/false: seven recognize terms and three connect related ideas. No calculations or code tracing are required.\n"
   ]
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    "\n",
    "<div class='ch13-preview-quiz' id='ch13-preview-quiz' data-question-set-version='dsm-ch13-preview-2026-10-19-v2'>\n",
    "  <p>Earlier submissions and best scores are retained. If you already completed this Preview, you do not need to repeat it; you may retry the revised questions.</p>\n",
    "  <div id='ch13-preview-questions'></div>\n",
    "  <div class='ch13-preview-actions'>\n",
    "    <button type='button' id='ch13-preview-submit' disabled>Submit</button>\n",
    "    <button type='button' class='secondary' id='ch13-preview-reset'>Reset</button>\n",
    "    <span class='ch13-preview-result' id='ch13-preview-result' aria-live='polite'></span>\n",
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    "\n",
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    "\n",
    "  function draftAnswers(quiz) {\n",
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    "  var questions = [\n",
    "  {\n",
    "    \"format\": \"true_false\",\n",
    "    \"prompt\": \"True or false: Multiple regression means predicting several target variables while using only one predictor.\",\n",
    "    \"concepts\": [\n",
    "      \"Multiple regression\",\n",
    "      \"Predictor\",\n",
    "      \"Target\"\n",
    "    ],\n",
    "    \"explanation\": \"False. In this chapter, multiple regression predicts a target using more than one predictor. The word multiple refers to the input predictors, not to several target outcomes.\",\n",
    "    \"retry_hint\": \"Check what becomes multiple in the chapter's model: inputs or target outcomes.\",\n",
    "    \"id\": \"q1\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1302-multiple-regression.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"True\",\n",
    "      \"B\": \"False\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"true_false\",\n",
    "    \"prompt\": \"True or false: A predictor is an input variable supplied to a model.\",\n",
    "    \"concepts\": [\n",
    "      \"Predictor\",\n",
    "      \"Target\"\n",
    "    ],\n",
    "    \"explanation\": \"True. Predictors supply information used by the model. The target is the outcome being modeled; a coefficient is a fitted model parameter rather than an input observation.\",\n",
    "    \"retry_hint\": \"Separate input variables, output variables, and fitted model parameters.\",\n",
    "    \"id\": \"q2\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1301-linear-regression.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"True\",\n",
    "      \"B\": \"False\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"prompt\": \"A housing model uses floor area and age to predict sale price. In this model, sale price is the:\",\n",
    "    \"concepts\": [\n",
    "      \"Target\",\n",
    "      \"Predictor\"\n",
    "    ],\n",
    "    \"explanation\": \"Sale price is the outcome the model aims to predict, so it is the target. Floor area and age are predictors. Coefficients describe how the fitted model uses those predictors.\",\n",
    "    \"retry_hint\": \"Identify the quantity the model is trying to predict.\",\n",
    "    \"id\": \"q3\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1302-multiple-regression.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Feature matrix\",\n",
    "      \"B\": \"Predictor\",\n",
    "      \"C\": \"Target\",\n",
    "      \"D\": \"Coefficient\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"prompt\": \"What is the fitted model parameter attached to a predictor called?\",\n",
    "    \"concepts\": [\n",
    "      \"Coefficient\",\n",
    "      \"Predictor\"\n",
    "    ],\n",
    "    \"explanation\": \"A coefficient is a model parameter associated with a predictor. An observation supplies data, the response vector holds target values, and a test case is reserved for evaluation.\",\n",
    "    \"retry_hint\": \"Distinguish a fitted parameter from data rows and stored target values.\",\n",
    "    \"id\": \"q4\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1302-multiple-regression.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Observation\",\n",
    "      \"B\": \"Coefficient\",\n",
    "      \"C\": \"Response vector\",\n",
    "      \"D\": \"Test case\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"prompt\": \"Which object contains the input predictor values for all the observations used in a model?\",\n",
    "    \"concepts\": [\n",
    "      \"Feature matrix\",\n",
    "      \"Response vector\"\n",
    "    ],\n",
    "    \"explanation\": \"The feature matrix organizes predictor values by observation and feature. The response vector contains the corresponding target values. Their roles differ even when they describe the same observations.\",\n",
    "    \"retry_hint\": \"Compare the data structure holding inputs with the one holding outcomes.\",\n",
    "    \"id\": \"q5\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1301-linear-regression.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Response vector\",\n",
    "      \"B\": \"Single residual\",\n",
    "      \"C\": \"Intercept\",\n",
    "      \"D\": \"Feature matrix\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"prompt\": \"A model fits its training data closely but predicts new cases poorly. Which term names this problem?\",\n",
    "    \"concepts\": [\n",
    "      \"Overfitting\",\n",
    "      \"Training data\",\n",
    "      \"Test data\"\n",
    "    ],\n",
    "    \"explanation\": \"Overfitting means adapting too closely to the training data, including noise that does not transfer well. Strong performance on familiar data alone is therefore not evidence of good generalization.\",\n",
    "    \"retry_hint\": \"Compare performance on familiar training cases with performance on new cases.\",\n",
    "    \"id\": \"q6\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1301-linear-regression.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Holding constant\",\n",
    "      \"B\": \"Overfitting\",\n",
    "      \"C\": \"Additivity\",\n",
    "      \"D\": \"Interpretability\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"prompt\": \"Two predictors in a model are strongly associated with each other. Which term describes that relationship?\",\n",
    "    \"concepts\": [\n",
    "      \"Multicollinearity\",\n",
    "      \"Predictor\"\n",
    "    ],\n",
    "    \"explanation\": \"Multicollinearity is strong association among predictors. It concerns relationships between model inputs, rather than the difference between predictions and outcomes or the division into training and test data.\",\n",
    "    \"retry_hint\": \"Focus on the relationship among predictors rather than between a prediction and its error.\",\n",
    "    \"id\": \"q7\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1302-multiple-regression.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"A residual diagnostic\",\n",
    "      \"B\": \"A train/test split\",\n",
    "      \"C\": \"Multicollinearity\",\n",
    "      \"D\": \"An intercept\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"true_false\",\n",
    "    \"prompt\": \"True or false: Reserved test data evaluate a model using cases that were not used to fit it.\",\n",
    "    \"concepts\": [\n",
    "      \"Training data\",\n",
    "      \"Test data\"\n",
    "    ],\n",
    "    \"explanation\": \"True. Training and test data have different roles. Holding cases out of fitting provides a more informative check of prediction on new cases than measuring fit only on the training data.\",\n",
    "    \"retry_hint\": \"Connect the reason for reserving data with the difference between fitting and evaluating.\",\n",
    "    \"id\": \"q8\",\n",
    "    \"cognitive_level\": \"connection\",\n",
    "    \"reading\": \"../1301-linear-regression.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"True\",\n",
    "      \"B\": \"False\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"prompt\": \"A manager interprets the floor-area coefficient while keeping home age fixed in the model comparison. Which idea does this illustrate?\",\n",
    "    \"concepts\": [\n",
    "      \"Holding constant\",\n",
    "      \"Coefficient\",\n",
    "      \"Predictor\"\n",
    "    ],\n",
    "    \"explanation\": \"Holding constant isolates the fitted model comparison associated with one predictor while fixing the others. It describes coefficient interpretation within the model; it does not by itself establish a causal effect.\",\n",
    "    \"retry_hint\": \"Pay attention to which predictor changes and which predictors are kept fixed.\",\n",
    "    \"id\": \"q9\",\n",
    "    \"cognitive_level\": \"connection\",\n",
    "    \"reading\": \"../1302-multiple-regression.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Changing all predictors together\",\n",
    "      \"B\": \"Treating a coefficient as the target\",\n",
    "      \"C\": \"Ignoring all predictors except the intercept\",\n",
    "      \"D\": \"Holding other predictors constant\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"prompt\": \"Two models predict similarly well, but a manager can explain one model's reasoning much more clearly. Which consideration distinguishes them?\",\n",
    "    \"concepts\": [\n",
    "      \"Interpretability\",\n",
    "      \"Prediction pipeline\"\n",
    "    ],\n",
    "    \"explanation\": \"Interpretability concerns how readily a model can be explained. Similar predictive performance does not imply equal ease of explaining why the models produce their predictions.\",\n",
    "    \"retry_hint\": \"Separate predictive performance from how understandable a model is to its users.\",\n",
    "    \"id\": \"q10\",\n",
    "    \"cognitive_level\": \"connection\",\n",
    "    \"reading\": \"../1301-linear-regression.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Interpretability\",\n",
    "      \"B\": \"Training fit\",\n",
    "      \"C\": \"Predictive accuracy\",\n",
    "      \"D\": \"Proof of causality\"\n",
    "    }\n",
    "  }\n",
    "];\n",
    "\n",
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    "    \"prompt\": \"Which term matches this explanation? Regression with more than one predictor.\",\n",
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    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1300-multiple-regression.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q3\",\n",
    "    \"prompt\": \"Which term matches this explanation? The predicted target when all predictors equal zero.\",\n",
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    "      \"A\": \"Multiple regression\",\n",
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    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1300-multiple-regression.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q4\",\n",
    "    \"prompt\": \"Which term matches this explanation? The target values used for modeling.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Multiple regression\",\n",
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    "      \"C\": \"Target\",\n",
    "      \"D\": \"Predictor\"\n",
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    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Response vector\"\n",
    "    ],\n",
    "    \"explanation\": \"Response vector: The target values used for modeling. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1300-multiple-regression.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q5\",\n",
    "    \"prompt\": \"Which term matches this explanation? A model assumption that predictor effects combine by addition.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Target\",\n",
    "      \"B\": \"Multiple regression\",\n",
    "      \"C\": \"Predictor\",\n",
    "      \"D\": \"Additivity\"\n",
    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Additivity\"\n",
    "    ],\n",
    "    \"explanation\": \"Additivity: A model assumption that predictor effects combine by addition. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1300-multiple-regression.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q6\",\n",
    "    \"prompt\": \"Which term matches this explanation? Observed value minus predicted value.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Multiple regression\",\n",
    "      \"B\": \"Residual\",\n",
    "      \"C\": \"Predictor\",\n",
    "      \"D\": \"Target\"\n",
    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Residual\"\n",
    "    ],\n",
    "    \"explanation\": \"Residual: Observed value minus predicted value. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1300-multiple-regression.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q7\",\n",
    "    \"prompt\": \"Which term matches this explanation? Data used to fit a model.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Multiple regression\",\n",
    "      \"B\": \"Predictor\",\n",
    "      \"C\": \"Training data\",\n",
    "      \"D\": \"Target\"\n",
    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Training data\"\n",
    "    ],\n",
    "    \"explanation\": \"Training data: Data used to fit a model. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1300-multiple-regression.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q8\",\n",
    "    \"prompt\": \"Which term matches this explanation? Square root of mean squared prediction error.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Root mean squared error\",\n",
    "      \"B\": \"Predictor\",\n",
    "      \"C\": \"Target\",\n",
    "      \"D\": \"Multiple regression\"\n",
    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Root mean squared error\"\n",
    "    ],\n",
    "    \"explanation\": \"Root mean squared error: Square root of mean squared prediction error. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1300-multiple-regression.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q9\",\n",
    "    \"prompt\": \"Which term matches this explanation? When a model fits training data too closely and generalizes poorly.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Target\",\n",
    "      \"B\": \"Multiple regression\",\n",
    "      \"C\": \"Predictor\",\n",
    "      \"D\": \"Overfitting\"\n",
    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Overfitting\"\n",
    "    ],\n",
    "    \"explanation\": \"Overfitting: When a model fits training data too closely and generalizes poorly. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1300-multiple-regression.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q10\",\n",
    "    \"prompt\": \"Which term matches this explanation? The steps used to prepare data, fit a model, and evaluate predictions.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Prediction pipeline\",\n",
    "      \"B\": \"Multiple regression\",\n",
    "      \"C\": \"Predictor\",\n",
    "      \"D\": \"Target\"\n",
    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Prediction pipeline\"\n",
    "    ],\n",
    "    \"explanation\": \"Prediction pipeline: The steps used to prepare data, fit a model, and evaluate predictions. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1300-multiple-regression.html\"\n",
    "  }\n",
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    "  }\n",
    "\n",
    "  function loadSessionIdentity(identity, actions, submit, result) {\n",
    "    submit.disabled = true;\n",
    "    actions.classList.add('is-locked');\n",
    "    result.textContent = 'Sign in from the account menu to submit this assignment.';\n",
    "\n",
    "    return fetch('/api/v1/session.php', { credentials: 'same-origin' })\n",
    "      .then(function (response) { return response.ok ? response.json() : null; })\n",
    "      .then(function (payload) {\n",
    "        if (!payload || !payload.authenticated || !payload.identity) return identity;\n",
    "        identity.canvas_user_id = payload.identity.canvas_user_id || identity.canvas_user_id || '';\n",
    "        identity.student_identifier = payload.identity.student_identifier || identity.student_identifier || '';\n",
    "        submit.disabled = false;\n",
    "        actions.classList.remove('is-locked');\n",
    "        result.textContent = payload.identity.display_name ? 'Signed in as ' + payload.identity.display_name + '.' : 'Signed in.';\n",
    "        return identity;\n",
    "      })\n",
    "      .catch(function () { return identity; });\n",
    "  }\n",
    "\n",
    "  function renderQuestions(container) {\n",
    "    container.textContent = '';\n",
    "    questions.forEach(function (question, index) {\n",
    "      var card = document.createElement('div');\n",
    "      card.className = 'ch13-preview-question';\n",
    "      card.dataset.question = question.id;\n",
    "\n",
    "      var prompt = document.createElement('p');\n",
    "      prompt.appendChild(text((index + 1) + '. ' + question.prompt));\n",
    "      card.appendChild(prompt);\n",
    "\n",
    "      (attemptState ? attemptState.orders[question.id] : Object.keys(question.choices)).forEach(function (letter, position) {\n",
    "        var label = document.createElement('label');\n",
    "        var input = document.createElement('input');\n",
    "        input.type = 'radio';\n",
    "        input.name = question.id;\n",
    "        input.value = letter;\n",
    "        input.checked = !!(attemptState && attemptState.answers[question.id] === letter);\n",
    "        label.appendChild(input);\n",
    "        label.appendChild(text(String.fromCharCode(65 + position) + '. ' + question.choices[letter]));\n",
    "        card.appendChild(label);\n",
    "      });\n",
    "\n",
    "      var feedback = document.createElement('div');\n",
    "      feedback.className = 'ch13-preview-feedback';\n",
    "      feedback.setAttribute('aria-live', 'polite');\n",
    "      card.appendChild(feedback);\n",
    "      container.appendChild(card);\n",
    "    });\n",
    "  }\n",
    "\n",
    "  function collectAnswers(quiz) {\n",
    "    var answers = {};\n",
    "    questions.forEach(function (question) {\n",
    "      var selected = quiz.querySelector('input[name=' + question.id + ']:checked');\n",
    "      answers[question.id] = selected ? selected.value : '';\n",
    "    });\n",
    "    // Press stores this marker with the submitted answers; it is not a scored question.\n",
    "    answers.__question_set = attemptState ? attemptState.version : questionSetVersion;\n",
    "    if (attemptState) answers.preview_attempt = attemptState.token;\n",
    "    return answers;\n",
    "  }\n",
    "\n",
    "  function loadFeedbackPolicy() {\n",
    "    // Use the existing server release setting; a network failure must not unlock answers.\n",
    "    return fetch('/api/v1/assignment-settings.php?assignment_id=' + encodeURIComponent(quizId), {\n",
    "      credentials: 'same-origin'\n",
    "    })\n",
    "      .then(function (response) { return response.ok ? response.json() : null; })\n",
    "      .then(function (payload) {\n",
    "        answersUnlocked = !!(payload && payload.ok && payload.answers_unlocked === true);\n",
    "      })\n",
    "      .catch(function () { answersUnlocked = false; });\n",
    "  }\n",
    "\n",
    "  function applyFeedback(quiz, feedback) {\n",
    "    questions.forEach(function (question) {\n",
    "      var card = quiz.querySelector('[data-question=' + question.id + ']');\n",
    "      var message = card.querySelector('.ch13-preview-feedback');\n",
    "      var item = feedback[question.id];\n",
    "      message.className = 'ch13-preview-feedback';\n",
    "      var status = (!item || !item.submitted) ? 'No answer submitted.' :\n",
    "        (item.correct ? 'Correct.' : 'Review and try again.');\n",
    "      var guidance = answersUnlocked ? question.explanation : question.retry_hint;\n",
    "      message.textContent = status + ' ' + guidance;\n",
    "      var reading = document.createElement('a');\n",
    "      reading.href = question.reading || \"../1300-multiple-regression.html\";\n",
    "      reading.appendChild(text('Review this concept'));\n",
    "      message.appendChild(text(' '));\n",
    "      message.appendChild(reading);\n",
    "      message.classList.add(item && item.correct ? 'correct' : 'incorrect');\n",
    "    });\n",
    "  }\n",
    "\n",
    "  function initLegacyPreviewQuiz() {\n",
    "    var quiz = document.getElementById('ch13-preview-quiz');\n",
    "    if (!quiz || quiz.dataset.ready === 'true') return;\n",
    "    quiz.dataset.ready = 'true';\n",
    "\n",
    "    var identity = getParams();\n",
    "    var questionsContainer = document.getElementById('ch13-preview-questions');\n",
    "    var result = document.getElementById('ch13-preview-result');\n",
    "    var submit = document.getElementById('ch13-preview-submit');\n",
    "    var actions = quiz.querySelector('.ch13-preview-actions');\n",
    "    var reset = document.getElementById('ch13-preview-reset');\n",
    "\n",
    "    renderQuestions(questionsContainer);\n",
    "    loadSessionIdentity(identity, actions, submit, result);\n",
    "\n",
    "    submit.addEventListener('click', function () {\n",
    "      var answers = collectAnswers(quiz);\n",
    "      submit.disabled = true;\n",
    "      result.textContent = 'Submitting...';\n",
    "\n",
    "      fetch('/api/v1/quiz-attempts.php', {\n",
    "        method: 'POST',\n",
    "        headers: { 'Content-Type': 'application/json' },\n",
    "        credentials: 'same-origin',\n",
    "        body: JSON.stringify({\n",
    "          quiz_id: quizId,\n",
    "          question_set_version: questionSetVersion,\n",
    "          answers: answers,\n",
    "          student_identifier: identity.student_identifier || identity.canvas_user_id || '',\n",
    "          canvas_course_id: identity.canvas_course_id,\n",
    "          canvas_assignment_id: identity.canvas_assignment_id,\n",
    "          canvas_user_id: identity.canvas_user_id\n",
    "        })\n",
    "      })\n",
    "        .then(function (response) {\n",
    "          return response.text().then(function (text) {\n",
    "            var payload = null;\n",
    "            try {\n",
    "              payload = text ? JSON.parse(text) : null;\n",
    "            } catch (error) {\n",
    "              throw new Error('Server returned a non-JSON response (HTTP ' + response.status + '): ' + text.slice(0, 160));\n",
    "            }\n",
    "            if (!payload) {\n",
    "              throw new Error('Server returned an empty response (HTTP ' + response.status + '). Check that PHP is enabled for /api/v1/quiz-attempts.php.');\n",
    "            }\n",
    "            if (!response.ok || !payload.ok) {\n",
    "              throw new Error(payload.message || payload.error || 'Submission failed.');\n",
    "            }\n",
    "            return payload;\n",
    "          });\n",
    "        })\n",
    "        .then(function (payload) {\n",
    "          var best = (payload.best_score === null || typeof payload.best_score === 'undefined') ? payload.score : payload.best_score;\n",
    "          var attempt = (payload.attempt_count === null || typeof payload.attempt_count === 'undefined') ? '' : ' Attempt ' + payload.attempt_count + '.';\n",
    "          return loadFeedbackPolicy().then(function () {\n",
    "            applyFeedback(quiz, payload.feedback || {});\n",
    "            result.textContent = 'Submission saved.' + attempt + ' Score: ' + payload.score + ' / ' + payload.max_score + '. Best score: ' + best + ' / ' + payload.max_score + '. Canvas sync: ' + payload.canvas_sync_status + '.';\n",
    "            if (!answersUnlocked) result.textContent += ' Full explanations are available when answers are released.';\n",
    "          });\n",
    "        })\n",
    "        .catch(function (error) {\n",
    "          result.textContent = 'Could not save this attempt: ' + error.message;\n",
    "        })\n",
    "        .finally(function () {\n",
    "          submit.disabled = false;\n",
    "        });\n",
    "    });\n",
    "\n",
    "    reset.addEventListener('click', function () {\n",
    "      quiz.querySelectorAll('input[type=radio]').forEach(function (input) {\n",
    "        input.checked = false;\n",
    "      });\n",
    "      quiz.querySelectorAll('.ch13-preview-feedback').forEach(function (feedback) {\n",
    "        feedback.className = 'ch13-preview-feedback';\n",
    "        feedback.textContent = '';\n",
    "      });\n",
    "      result.textContent = '';\n",
    "    });\n",
    "  }\n",
    "\n",
    "\n",
    "  function initPreviewQuiz() {\n",
    "    // The legacy PHP host retains its existing fixed-order delivery until it migrates to Press.\n",
    "    if (!/(^|\\.)thinkpress\\.org$/.test(window.location.hostname) &&\n",
    "        !['localhost', '127.0.0.1'].includes(window.location.hostname)) return initLegacyPreviewQuiz();\n",
    "    var quiz = document.getElementById('ch13-preview-quiz');\n",
    "    if (!quiz || quiz.dataset.ready === 'true') return;\n",
    "    quiz.dataset.ready = 'true';\n",
    "\n",
    "    var identity = getParams();\n",
    "    var questionsContainer = document.getElementById('ch13-preview-questions');\n",
    "    var result = document.getElementById('ch13-preview-result');\n",
    "    var submit = document.getElementById('ch13-preview-submit');\n",
    "    var actions = quiz.querySelector('.ch13-preview-actions');\n",
    "    var reset = document.getElementById('ch13-preview-reset');\n",
    "\n",
    "    // Press owns this quiz's draft and option order; the generic runner must not restore older inputs over it.\n",
    "    quiz.classList.add('press-preview-managed');\n",
    "    var next = document.createElement('button');\n",
    "    next.type = 'button';\n",
    "    next.textContent = 'Start a new attempt';\n",
    "    next.hidden = true;\n",
    "    actions.appendChild(next);\n",
    "\n",
    "    function lockQuestions(locked) {\n",
    "      quiz.querySelectorAll('input[type=radio]').forEach(function (input) { input.disabled = locked; });\n",
    "      reset.disabled = locked;\n",
    "    }\n",
    "    function showState(payload) {\n",
    "      questions = attemptState.questions;\n",
    "      renderQuestions(questionsContainer);\n",
    "      lockQuestions(payload.completed);\n",
    "      submit.disabled = payload.completed;\n",
    "      next.hidden = !payload.completed;\n",
    "      if (!payload.completed) result.textContent = '';\n",
    "      if (attemptState.preserved_draft && !payload.completed) {\n",
    "        result.textContent = 'Resumed your saved answers with their original option order.';\n",
    "      }\n",
    "      if (payload.result) {\n",
    "        return loadFeedbackPolicy().then(function () {\n",
    "          applyFeedback(quiz, payload.result.feedback || {});\n",
    "          result.textContent = 'Saved attempt. Score: ' + payload.result.score + ' / ' + payload.result.max_score +\n",
    "            '. Best score: ' + payload.result.best_score + ' / ' + payload.result.max_score + '.';\n",
    "          if (!answersUnlocked) result.textContent += ' Full explanations are available when answers are released.';\n",
    "        });\n",
    "      }\n",
    "      return Promise.resolve();\n",
    "    }\n",
    "    renderQuestions(questionsContainer);\n",
    "    lockQuestions(true);\n",
    "    loadSessionIdentity(identity, actions, submit, result).then(function () {\n",
    "      if (submit.disabled) return;\n",
    "      submit.disabled = true;\n",
    "      result.textContent = 'Resuming your Preview...';\n",
    "      return stateRequest('resume').then(showState).catch(function (error) {\n",
    "        submit.disabled = true;\n",
    "        result.textContent = 'Could not resume this Preview: ' + error.message + ' Reload to retry.';\n",
    "      });\n",
    "    });\n",
    "\n",
    "    quiz.addEventListener('change', function (event) {\n",
    "      if (!event.target || event.target.type !== 'radio' || !attemptState) return;\n",
    "      saveAnswers(quiz).catch(function (error) { result.textContent = 'Answers not saved: ' + error.message; });\n",
    "    });\n",
    "\n",
    "    submit.addEventListener('click', async function () {\n",
    "      submit.disabled = true;\n",
    "      lockQuestions(true);\n",
    "      result.textContent = 'Submitting...';\n",
    "      try {\n",
    "        await saveAnswers(quiz);\n",
    "        var response = await fetch('/api/v1/quiz-attempts.php', {\n",
    "          method: 'POST', headers: { 'Content-Type': 'application/json' }, credentials: 'same-origin',\n",
    "          body: JSON.stringify({ quiz_id: quizId, answers: collectAnswers(quiz),\n",
    "            question_set_version: attemptState.version,\n",
    "            student_identifier: identity.student_identifier || identity.canvas_user_id || '',\n",
    "            canvas_course_id: identity.canvas_course_id, canvas_assignment_id: identity.canvas_assignment_id,\n",
    "            canvas_user_id: identity.canvas_user_id })\n",
    "        });\n",
    "        var payload = await response.json();\n",
    "        if (!response.ok || !payload.ok) throw new Error(payload.message || payload.error || 'Submission failed.');\n",
    "        await loadFeedbackPolicy();\n",
    "        applyFeedback(quiz, payload.feedback || {});\n",
    "        result.textContent = 'Submission saved. Attempt ' + payload.attempt_count + '. Score: ' + payload.score +\n",
    "          ' / ' + payload.max_score + '. Best score: ' + payload.best_score + ' / ' + payload.max_score + '.';\n",
    "        if (!answersUnlocked) result.textContent += ' Full explanations are available when answers are released.';\n",
    "        next.hidden = false;\n",
    "      } catch (error) {\n",
    "        result.textContent = 'Could not save this attempt: ' + error.message;\n",
    "        submit.disabled = false;\n",
    "        lockQuestions(false);\n",
    "      }\n",
    "    });\n",
    "\n",
    "    reset.addEventListener('click', function () {\n",
    "      submit.disabled = true;\n",
    "      stateQueue = stateQueue.catch(function () {}).then(function () { return stateRequest('clear'); });\n",
    "      stateQueue.then(function (payload) { result.textContent = ''; return showState(payload); })\n",
    "        .catch(function (error) { result.textContent = error.message; submit.disabled = false; });\n",
    "    });\n",
    "    next.addEventListener('click', function () {\n",
    "      next.disabled = true;\n",
    "      stateRequest('next').then(function (payload) { result.textContent = ''; return showState(payload); })\n",
    "        .catch(function (error) { result.textContent = error.message; })\n",
    "        .finally(function () { next.disabled = false; });\n",
    "    });\n",
    "  }\n",
    "\n",
    "  if (document.readyState === 'loading') {\n",
    "    document.addEventListener('DOMContentLoaded', initPreviewQuiz);\n",
    "  } else {\n",
    "    initPreviewQuiz();\n",
    "  }\n",
    "})();\n",
    "</script>"
   ]
  }
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