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    thought i may as well ask you guys on the off chance that someone might actually understand this :\ its a bit of an epic read...

    im trying to finish my lab report for my 1st yr psychology degree, but i missed a whole load of lectures on it and now ive got to interpret these results and havnt a clueee what the heck its on about

    Its about visual illusions such as the ponzo task and the Muller-Lyer


    (basically one line looks longer than the other, even though theyre the same). Some guy called gregory proposed that we are fooled by them because we see a 3D representation within the 2D image, ie the ponzo is train-tracks receding into the distance, and our knowledge of depth reminds us that 'the track furthest in the distance' should be shorter, thus it looks too long.

    SOOOooo, the experiment we did was flipping this on its head; if subjects are given what is clearly a representation of a 3D scene, can they see it as 2D?
    THe image they were given was this:


    (not actually this pic but close enough...)
    and they were asked to state whether they thought the street was uphill, downhill or level, and to draw the sloping line of the lefthand kerb. participants were then divided into 3 groups - on was told it is in fact uphill, one was told it was downhill and the other that it was level. again they drew the kerb line. participants that did not originally see the street as level before priming were disqualified from the study, and the averages and stuff were taken. we compared the angle that the participants drew the kerb before and after priming. there are also a load of p values from a t-test, i should know what they mean, but somewhere along the way i didnt learnt that :confused:

    p=0.12 for those told it was uphill, p=0.07 for those told it was downhill and p=0.32 for those told it was level WHAT THE **** DOES THAT MEAN?!!?!?!?

    and what does this whole thing prove/disprove?? so what if they drew it steeper or shallower following priming? im guessing its because saying 'uphill' and 'downhill' makes pp think of hills, so that the representation of a 3D street can be seen as a hill, thus an image on the x-y plane (2D), but im really not sure, any other suggestions would be more than welcome :confused:
    and the p values, does that make it valid, invalid, are t-tests even about validity??

    cannot express how much i will love you if you can explain this to me
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    Um... well i cant see the picture because apparently im not a member of your uni.
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    (Original post by kellybee)
    thought i may as well ask you guys on the off chance that someone might actually understand this :\ its a bit of an epic read...
    We can't see your image because it's hosted on your university's server and requires a login. You can attach it to a post here, which might help (click on the "Manage Attachments" button in the advanced post editor).
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    meh, that pics close enough
    its most just the p value stuff...
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    Doesn't the p value indicate whether or not something is statistically significant? I haven't done them in a long time, sorry.

    In any case I'm not sure what it would mean. Anyone from your course you can ask?
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    (Original post by Sweyn Forkbeard)
    Anyone from your course you can ask?
    its due in 9 tomorrow morning and theyre an anti-social lot, dont think theyd take too kindly to me harrassing them about it now...
    its gonna be a long night
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    I doubt this helps, but: http://en.wikipedia.org/wiki/Statistical_significance

    Is it the actual t-test that is giving you trouble, or what it would mean if the results were significant or not?
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    usually if p is less than 0.05 it is significant, none of your values are - therefore it is non-significant. seems like the point of the coursework is to find out if information given after initial viewing can change your perception, and create an illusion. those who were told it was level didn't significantly change their perceptions (0.32), those who were told it was uphill and downhill (0.12 and 0.07 respectively) changed their perceptions more so, but not to a significant extent. therefore the information given wasn't enough to change their perceptions significantly. in your discussions you can say how some illusions are limited to 2d perceptions, or criticise the procedure saying the priming wasn't strong enough. things like that. we had a v. similar first year coursework piece, and it's easier than it seems once you get a hang of the terminology. good luck.
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    Your thread-title poses something of a dilemma.
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    (Original post by thomasisaacsini)
    usually if p is less than 0.05 it is significant, none of your values are - therefore it is non-significant. seems like the point of the coursework is to find out if information given after initial viewing can change your perception, and create an illusion. those who were told it was level didn't significantly change their perceptions (0.32), those who were told it was uphill and downhill (0.12 and 0.07 respectively) changed their perceptions more so, but not to a significant extent. therefore the information given wasn't enough to change their perceptions significantly. in your discussions you can say how some illusions are limited to 2d perceptions, or criticise the procedure saying the priming wasn't strong enough. things like that. we had a v. similar first year coursework piece, and it's easier than it seems once you get a hang of the terminology. good luck.

    thanks!!
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    (Original post by kellybee)
    p=0.12 for those told it was uphill, p=0.07 for those told it was downhill and p=0.32 for those told it was level WHAT THE **** DOES THAT MEAN?!!?!?!?

    and the p values, does that make it valid, invalid, are t-tests even about validity??
    For a mean to differ significantly at a 5% level, you need p < 0.05. You seem to have three p-values which is rather odd as I thought the "level" group would have been your control? If not, what was? I.e., what comparisons are you making in your t-tests to obtain those p-values?

    Wouldn't an ANOVA have been better instead of 3 t-tests? Your risk of type I error is going to be pretty high.

    PS. I love how you're only just writing up your discussion a few hours before your deadline (without catching up on missed lectures). Great way to start your first year.
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    (Original post by GodspeedGehenna)
    For a mean to differ significantly at a 5% level, you need p < 0.05. You seem to have three p-values which is rather odd as I thought the "level" group would have been your control? If not, what was? I.e., what comparisons are you making in your t-tests to obtain those p-values?

    Wouldn't an ANOVA have been better instead of 3 t-tests? Your risk of type I error is going to be pretty high.

    PS. I love how you're only just writing up your discussion a few hours before your deadline (without catching up on missed lectures). Great way to start your first year.
    i thinks its safe to say i will not be passing this year.:yep:
 
 
 
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