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    Ok, here is the data:

    conditions Observable Number
    Dark,Light 51
    Dark,Dry 186
    Wet,Light 46
    Wet,Dark 177

    Ok, the null hypothesis is that the conditions do not affect the observable number of woodlice seen in each environment

    so expected numbers is the total divided by 4 = 115

    can someone calculate chi squared and tell me what they got so i can compare?
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    wowzer i got 154.278... which seems ridiculously high, especially as the degrees of freedom is really low (3)
    what did you get?
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    χ2(1) = 0.0548
    p = 0.8149 (two-tailed)
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    (Original post by nellydee)
    wowzer i got 154.278... which seems ridiculously high, especially as the degrees of freedom is really low (3)
    what did you get?
    i got that as well! for the degrees of freedom, i left out some data. here is the link to the full table. so the degrees of freedom is 18, no?

    http://www.thestudentroom.co.uk/show....php?t=1164545
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    (Original post by GodspeedGehenna)
    χ2(1) = 0.0548
    p = 0.8149 (two-tailed)
    how?! can you do a worked solution?
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    That's not how you work out the expected values.
    You have to keep the column, row and grand totals the same, and work it out in ratio: E = \frac{(row total)(column total)}{grand total}
    That way you can calculate \chi^2 = \displaystyle\Sigma\dfrac{(|O-E|-\frac{1}{2})^2}{E}

    I hate stats :nothing:
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    (Original post by maxfire)
    That's not how you work out the expected values.
    You have to keep the column, row and grand totals the same, and work it out in ratio: E = \frac{(row total)(column total)}{grand total}
    That way you can calculate \chi^2 = \displaystyle\Sigma\dfrac{(|O-E|-\frac{1}{2})^2}{E}

    I hate stats :nothing:
    if the null hyp says there is an equal chance that they go in any of the four areas, doesnt it mean that the expected values are just 1/4 of the total? by the way...my childhood is ruined now
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    (Original post by maxfire)
    That's not how you work out the expected values.
    You have to keep the column, row and grand totals the same, and work it out in ratio: E = \frac{(row total)(column total)}{grand total}
    That way you can calculate \chi^2 = \displaystyle\Sigma\dfrac{(|O-E|-\frac{1}{2})^2}{E}

    I hate stats :nothing:
    i think you're thinking of chi squared tests from s2, it's slightly different in s3. :yy:
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    maths make me hurt
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    (Original post by angrydanmarin)
    maths make me hurt
    same....
 
 
 
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