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{
    "url": "https://numbas.mathcentre.ac.uk/api/questions/11870/?format=api",
    "name": "Linear regression - find line of best fit given summary statistics, ",
    "published": true,
    "project": "https://numbas.mathcentre.ac.uk/api/projects/601/?format=api",
    "author": {
        "url": "https://numbas.mathcentre.ac.uk/api/users/697/?format=api",
        "profile": "https://numbas.mathcentre.ac.uk/accounts/profile/697/?format=api",
        "full_name": "Newcastle University Mathematics and Statistics",
        "pk": 697,
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    "edit": "https://numbas.mathcentre.ac.uk/question/11870/linear-regression-find-line-of-best-fit-given-summ/?format=api",
    "preview": "https://numbas.mathcentre.ac.uk/question/11870/linear-regression-find-line-of-best-fit-given-summ/preview/?format=api",
    "download": "https://numbas.mathcentre.ac.uk/question/11870/linear-regression-find-line-of-best-fit-given-summ.zip?format=api",
    "source": "https://numbas.mathcentre.ac.uk/question/11870/linear-regression-find-line-of-best-fit-given-summ.exam?format=api",
    "metadata": {
        "notes": "<p><strong>21/12/2012:</strong></p>\n    <p>Checked rounding, OK. Added tag cr1.</p>\n    <p>Possible use of scenarios, so added tag sc.</p>\n    <p>The array r2 generates the regression data which has an inbuilt noise via r1[x]+random(-9..9).</p>\n    <p>&nbsp;</p>",
        "licence": "Creative Commons Attribution 4.0 International",
        "description": "<p>Find a regression equation.</p>"
    },
    "status": "ok",
    "resources": []
}