424 stats - t test and chi square

Type one error

if you reject the null hypothesis but in the population the null hypothesis is actually true; false rejection error

same as significance level, .05 significance equals 5% of making type 1 error

What is the probability of making a Type 1 error?

type two error

if you retain the null but in the population the null hypothesis is actually false; false acceptance error

inversely

type 1 and 2 errors are _____ related

probability sampling, dv is interval and iv is nominal or ordinal, both samples N greater than 50

t-test assumptions

iv and dv must be ordinal or nominal, probability sampling

chi square assumptions

does not give information about strength of relationship, is sensitive to sample size, is sensitive to small expected frequencies

limitations of chi square

suggests weak relationship between variables and their correlation may be better explained by outside variables

spurious relationship (has to do with strength of dependence between variables)