￥兴兴补火称水我水的兴X聘H4<0Chapter-8Chi-square testYWSBo:μ=0火你我火大独%/
Chapter-8 Chi-square test
兴水茶兴林火称水的兴聘H:u<0I The mathematical propertiesYof chi-square distribution-WS Types of chi-square testsBo:μ=0> Chi-square test Chi-square distribution?火你水我火一独的兴一/L2
Ⅰ The mathematical properties of chi-square distribution Types of chi-square tests Chi-square test Chi-square distribution
KTypes of chi-square testsH:u<O1. Tests of goodness-of-fitObserved frequencies of one variable are significantlydifferent from the expected frequencies of the samevariable.E.g.occurrences of heads andtails whileflippinga coin2. Chi-Square tests of independence( or relationship)Two variables are associated or independent of the other.E.g.association betweensmoking and lungcancer.23
1. Tests of goodness-of-fit Observed frequencies of one variable are significantly different from the expected frequencies of the same variable. E.g. occurrences of heads and tails while flipping a coin. 2. Chi-Square tests of independence( or relationship) Two variables are associated or independent of the other. E.g. association between smoking and lung cancer. Types of chi-square tests
KChi-squaretest:u<0The chi-square test of independence is probably themost frequently used hypothesis test in the medicineIn this chapter, we will use chi-square test to evaluate1O:Edifferences among population when the test variable isnominal, dichotomous, ordinal, or grouped interval.B3
✓ The chi-square test of independence is probably the most frequently used hypothesis test in the medicine. ✓ In this chapter, we will use chi-square test to evaluate differences among population when the test variable is nominal, dichotomous, ordinal, or grouped interval. Chi-square test
KIndependence DefinedHI:u<oTwo variables are independent if, for all cases, theclassification of a case into a particular category of onevariable (the group variable) has no effect on theprobability that the case will fall into any particularcategory of the second variable (the test variable)1:4=UWhen two variables are independent, there is norelationship between them. We would expect that thefrequency breakdowns of the test variable to be similarfor all groups
Independence Defined ✓ Two variables are independent if, for all cases, the classification of a case into a particular category of one variable (the group variable) has no effect on the probability that the case will fall into any particular category of the second variable (the test variable). ✓ When two variables are independent, there is no relationship between them. We would expect that the frequency breakdowns of the test variable to be similar for all groups