{
  "multiple_choice": [
    {
      "question": "Which of the following is the BEST example of data mining?",
      "options": [
        "A) Using a spreadsheet to calculate the average of a set of numbers.",
        "B) Sorting a list of names alphabetically.",
        "C) Analyzing customer purchase history to identify trends.",
        "D) Creating a bar chart to visualize sales data."
      ],
      "answer": "C"
    },
     {
      "question": "What is the primary purpose of data visualization?",
      "options": [
        "A) To make data more complex.",
        "B) To hide trends in data.",
        "C) To make trends and patterns easier to see and understand.",
        "D) To calculate statistical values."
      ],
      "answer": "C"
    }
  ],
  "free_response": {
    "question": "A school is collecting data on student participation in extracurricular activities. They want to analyze this data to understand which activities are most popular and if there is any correlation between activity choice and academic performance. Describe the steps they might take, including data collection, processing, and analysis. Be specific about the types of tools and techniques they could use.",
     "scoring_breakdown": [
        "1 point for describing a method of data collection (e.g., surveys, sign-up sheets).",
        "1 point for explaining how the data can be processed (e.g., using a spreadsheet to organize data).",
        "1 point for explaining how data can be filtered (e.g., by grade level or activity type).",
        "1 point for describing a data analysis technique (e.g., finding correlations between activities and grades).",
        "1 point for explaining how data visualization can be used to present the findings (e.g., creating a bar chart showing popularity of each activity)."
      ]
  }
}

{
  "multiple_choice": [
    {
      "question": "Which of the following best describes a 'trend' in data analysis?",
      "options": [
        "A) A single data point that is very different from the others.",
        "B) A repeating pattern in the data.",
        "C) A general direction in which something is changing over time.",
        "D) A relationship between two different variables."
      ],
      "answer": "C"
    },
    {
      "question": "What is the important distinction to remember when interpreting correlations?",
      "options": [
        "A) Correlation always implies causation.",
        "B) Correlation does not equal causation.",
        "C) Correlations are only useful for small datasets.",
        "D) Correlations are always negative."
      ],
      "answer": "B"
    }
  ],
  "free_response": {
    "question": "A company has collected sales data for the past five years. Describe three different types of analysis they could perform on this data to gain insights. For each type of analysis, explain what kind of information they might uncover and how it could be useful for the company.",
     "scoring_breakdown": [
        "1 point for identifying a type of analysis (e.g., trend analysis).",
        "1 point for explaining what information the analysis can uncover (e.g., identify increasing or decreasing sales over time).",
        "1 point for explaining how the information could be useful (e.g., make predictions about future sales).",
         "1 point for identifying a second type of analysis (e.g., pattern analysis).",
        "1 point for explaining what information the analysis can uncover (e.g., identify seasonal sales patterns).",
        "1 point for explaining how the information could be useful (e.g., adjust inventory based on seasonal demand).",
         "1 point for identifying a third type of analysis (e.g., outlier analysis).",
        "1 point for explaining what information the analysis can uncover (e.g., identify unusual sales spikes or dips).",
        "1 point for explaining how the information could be useful (e.g., investigate the reasons for unusual sales)."
      ]
  }
}