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Math Help - Singificance levels, critical values and p-value. Help!!!!

  1. #1
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    Singificance levels, critical values and p-value. Help!!!!

    Dear Maths wizards,

    Firstly, i hope my post is in the correct place.

    I am not a mathematician but for a paper i am writing on music and education, i have conducted a study to find out if music capital affects pupils' engagement in classroom music lessons.

    I am currently analysing my data which is what brought me to your forum. I have two variables: a pupil's level of Musical Capital [MC] and a pupil's level of engagement in lessons. Both of these variables have been coded into numeric form and i am looking at their relationship to see if MC affects engagement. I have so far done quite a lot of statistics research and i understand a lot more than i thought i would, but need a couple of things clarifying...

    Would you agree that with the data i have and the fact that im looking at a relationship between two variables, i can use a null-hypothesis, a significance level and a p-value? All these look good to me, but i feel like im asking the 'chicken and the egg' question. Which of these comes first? Would you write about a null-hypothesis in your findings of a study or before? Do you decide on a 0.01 or 0.05 depending on how reliable you think your hypothesis is or is there a formula you have to apply to it? Once you have got this, how do you find your p-value (and what exactly is a p-value?!)

    I have been reading about this all afternoon and just need some clarification.

    As i said, im sorry if i have posted this in the wrong thread...

    Any help on the questions i have asked as well as new advice would be so welcome.

    Thank you in advance for your help,

    Yours confusedly,

    Olivia
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  2. #2
    MHF Contributor matheagle's Avatar
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    I'd use regression on your two variables.
    Based on your statement 'to see if MC affects engagement'
    I would like to see if there is a positive slope when fitting the data.
    I'd use 'MC' as X and 'engagement' as Y.
    Testing to see if the slope is positive is the same as testing to see if there is a positive correlation.
    And we can use all kinds of models too, but I would start with y=\beta_0+\beta_1 x+\epsilon.
    I would just obtain the p-values of your tests and I might test for normality before I run those t tests.
    I don't think I'm a wizard, I never even played dungeons and dragons as a child.
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    Thank you for your advice! Yes, i have set the two variables on an X and Y axis and they present a positive correlation (0.74 correlation coefficient).

    As for the p-value, t-tests and testing for normality...

    the p-value i am using is 0.05 (95% sure the results could not be found by chance- is this correct?)

    i have an f-test value of 9.98904E-16, which i think means my variances are not equal, therefore i have to use un-equal variance in the t-test. (Am i on the right tracks?)

    I am not sure whether to use a one tailed or two tailed t-test. I do know the supposed direction of difference of my findings, but am i right in thinking its just safer to use a two tailed test in all cases?

    I have used excel to find out the t-test value which is 0.001117649. In fact, it is the same for a one-tailed and two-tailed test. What does this show me?

    Now that i have my t-test figure, what does it mean? Do you know of a good stats website that will tell me what this number is showing? Its all very well having it, but i would like to know how to use it!

    What did you mean by the 'test for normality'? Do you mean the p-value?

    Thank you again, and please yell if i'm on the wrong lines!
    Last edited by oliviagmmc; May 25th 2009 at 02:30 AM.
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  4. #4
    MHF Contributor matheagle's Avatar
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    I have no idea what your hypothesis is when you say that you you 'have an f-test value of 9.98904E-16'.
    You need to tell me what the hypotheses are and what you are trying to test.
    And I don't think you understand what a p-value is.
    It's the probability of being worse off than your test statistic.
    So I need the alternative hypothesis and the test stat to determine the p-value.
    But I also need to know what kind of test you're running.
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