Probability and Significance Flashcards
what is a null hypothesis?
a null hypothesis states that there is ‘no difference’ between conditions
‘there is no difference in the number of words spoken in five minutes between participants who drink coffee and those who don’t’
what do statistical test do?
they determine which hypothesis is ‘true’ and whether we accept or reject the null hypothesis
what is an alternative hypothesis?
a hypothesis which states the difference between the two variables
‘after drinking coffee, participants say more words in the next five minutes than participants who don’t drink the coffee’
what are statistical tests based on?
the basis of probability.
all statistical tests employ a significance level - the point that the researcher can claim to have discovered a large enough difference/ correlation within the data to claim an effect has been found. (the point at which they can reject the null hypothesis and accept the alternative hypothesis)
what is the usual level of significance in psychology?
0.05 or 5%
this means the probability that the observed effect (the result) occurred when there is no effect in the population is equal to or less than 5%
- means that even when a researcher claims to have found a significant difference/ correlation, there is still up to 5% chance that it isn’t true for the target population in which the sample was drawn
this is because psychologists can never be 100% certain about a particular test unless they have tested EVERYONE
what is the calculated value?
once the statistical test has been calculated, the result is a number - the calculated value
to check for significance - the calculated value is compared to the critical value
which is a number that tells us if we can reject the null hypothesis, and accept the alternative hypothesis
critical values
one tailed test if the hypothesis is directional
two tailed test for a non directional hypothesis
probability level double when the 2 tailed tests are used as they are a more conservative prediction
- the number of participants - appears of the N value in the table - some tests degrees of freedom are calculated instead
level of significance - 0.05 is standard level of significance
what is a type 1 error?
when the null hypothesis is rejected and the alternative is accepted when it should be the other way round because the null hypothesis is true
- often referred to as an optimistic error or false positive as the researcher claims to have found a significant difference/ correlation when one doesn’t exist
what is type 2 error
when null hypothesis is accepted but it should have been the alternative hypothesis because it is true - pessimistic error ‘false negative’
when are we mor elikely to make a type one error
if the signifncance level is too lenient/ high - 0.1, rather than 0.05
type 2 error is more likley if the signifncance level is too stringent /low e.g. 0.01 as potentially signifnicant values can be mussed
why use 0.05 signifncance level
best balances the risk of making type one or type 2 error
