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Thread: *Novice* Which test? Is one even possilble

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    *Novice* Which test? Is one even possilble




    Hi Everyone,

    I am a complete novice to the world of statistics and I'm not the best mathematician.

    I have the data of three different city zones that each had air temperature measured once every fifteen minutes overnight so:

    ..........Zone1.......Zone 2......Zone 3
    8pm:..... 8 degrees.....7...........6
    8:15:......8.1..............8.3.......6
    8:30:

    etc...

    I basically want to compare the means of each zone with one another to see if the difference is significant or random chance and I think it's a one way analysis of variance test I have to use but honestly I understand very little of the jargon in my spss guidebook and I'm not 100 % sure if I can even use a statistical test lolz so any help would be greatly appreciated.

    Rowhi

    P.s please excuse the typo in the title.
    Last edited by rowhi; 04-04-2014 at 09:45 AM. Reason: I typod on the title

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    ggplot2orBust
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    Re: *Novice* Which test? Is one even possilble

    From what I've read here I think you'll want to look at a repeated measures ANOVA as the previous temperature certainly correlates to the next within each zone. The repeated measures model would take care of this dependence issue for you. There are other approaches but I think this is probably the most straight forward, particularity within SPSS and your comfort level.

    PS I think you can edit the title. If not flag it for a moderator using the triangle exclamation icon (though you may not see this on your own post).
    "If you torture the data long enough it will eventually confess."
    -Ronald Harry Coase -

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    Re: *Novice* Which test? Is one even possilble


    Not sure, but don't the three zones represent just 3 cases ("subjects"
    in the analysis, instead of 3 levels of a grouping factor? This here
    appears to me like one wants to test e.g. whether work performance of
    Jack, Jill and John, measured 10 times a day, differs significantly.
    I am not sure as to what population(s) one could generalize the
    results.

    Just my 2pence

    K.

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