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{
    "url": "https://numbas.mathcentre.ac.uk/api/questions/11939/?format=api",
    "name": "Sampling with and without replaement - binomial, hypergeometric, and Poisson approximation, ",
    "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,
        "avatar": {
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        }
    },
    "edit": "https://numbas.mathcentre.ac.uk/question/11939/sampling-with-and-without-replaement-binomial-hype/?format=api",
    "preview": "https://numbas.mathcentre.ac.uk/question/11939/sampling-with-and-without-replaement-binomial-hype/preview/?format=api",
    "download": "https://numbas.mathcentre.ac.uk/question/11939/sampling-with-and-without-replaement-binomial-hype.zip?format=api",
    "source": "https://numbas.mathcentre.ac.uk/question/11939/sampling-with-and-without-replaement-binomial-hype.exam?format=api",
    "metadata": {
        "notes": "<p><strong>5/02/2013:</strong></p>\n    <p>First draft finished.</p>\n    <p>Uses the jstats hypergeometric function&nbsp;hypgeomcdf(m-1,N,k,n)</p>",
        "licence": "Creative Commons Attribution 4.0 International",
        "description": "<p>Three parts. A sample of size $n$ is taken from $N$ where $k$ of the items are known to be defective and the task is to find the probability that more than $m$ defectives are in the sample. First part is sampling with replacement (binomial), second is sampling without replacement, (hypergeometric) and the last part uses the Poisson approximation to the first part.</p>"
    },
    "status": null,
    "resources": []
}