research methods ; probability + significance

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PROBABILITY AND SIGNIFICANCE
GD
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- the null hypothesis
dfgdg
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what two things may hypotheses be?
directional / non-directional
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what may these two types of hypotheses also be referred to as?
alternative hypothesis
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why?
alternative to null hypothesis
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what does null hypothesis state?
there is no difference between conditions
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what determines which hypothesis is true + whether we accept or reject null?
stats test
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- levels of significance and probability
dfgd
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stats tests don't work on certainty but?
probability
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all stats tests emply a significance level which is?
pt at which researcher can claim to have discovered significant difference / correlation within data
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in other words pt @ which researcher cna do what?
reject null + accept alternative
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what is the usual level of significance?
5% / 0.05 / p < 0.05
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what does this mean?
probability that observed effect occured by chance is equal to / less than 5%
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in effect when researcher claims to have found difference / correlation there's still 5% chance
it was a fluke
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why can psychologists never b 100% certain about particular result?
they haven't tested all members of population under all possible circumstances
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for this reason conventional probability level is?
5%
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USE OF STATS TABLES
DFGDF
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- critical value
dfdf
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what is the calculated value?
number you get from the stats tet
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to check for stat significance what do you have to do with this?
compare to critical value
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what is the critical valy?
number that tells us whether or not we can reject the null and accept alternative
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- lower levels of significance
dfgd
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occasionally more stringent significance level used like 0.01 why?
may be human cost like drug trial or 'one-offs' thay couldnt be repeated
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in all research if there's a large difference between calculated / critical what will happen?
researcher will check more stringent levels
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and the lwoer the p value?
the more statistically significant
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TYPE I AND TYPE II ERRORS
DFG
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what is a type i error?
when null rejected and alternative accepted when should be other way round
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what kind of error is this also referred to as?
optomistic error / false positive
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why?
researcher claims to have fuond significant diff / correlation when one doesn't exist
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what is a typeii error?
null accepted but should have been alternative bc that was true
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also known as?
pessimistic error / false negative
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more likely to make type i error when significance level is?
too lenient like 10%
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and type ii more likely with significance?
too stringent like 1%
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so why did we land @ 5% level?
best balances risk of type i / type ii error
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- the null hypothesis

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dfgdg

Card 3

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what two things may hypotheses be?

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Card 4

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what may these two types of hypotheses also be referred to as?

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why?

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