Formula for Confidence Intervals and Conditions | STA 6166, Study notes of Data Analysis & Statistical Methods

Download Formula for Confidence Intervals and Conditions | STA 6166 and more Study notes Data Analysis & Statistical Methods in PDF only on Docsity! Formula for Confidence Intervals and Conditions Questions to Ask YOURSELF Confidence interval Condition(s) that MUST be satisfied. (Check to see if they are satisfied Before you use them.) These conditions also apply to corresponding test of hypothesis. H ow m an y p op u la ti on s? In d ep en d en t sa m p le s? P ar am et er (s ) of in te re st P op u la ti on v ar ia n ce s? O n e N ot A p p lic ab le  K n ow n 0 / 2X z n         Population standard deviation, 0 is known plus Normal population or large sample U n k n ow n ( / 2, n 1 S X t n          Population standard deviation,  is unknown plus (Almost) Normal population  / 2 p(1 p) p z n        np  10 and n(1-p)  10 T w o Y e s  1 -  2 K n ow n 2 2 X 0 Y0 / 2 X Y (X Y) z n n             Population standard deviations, X0 and Y0 are known plus Normal populationS or large sampleS Y e s U n k n ow n 2 2 X Y / 2 , df ) X Y S S (X Y) t n n            df = smaller of (nx – 1) and (ny – 1) Population standard deviations, X and Y are unknown, unequal plus (Almost) normal populations N o D ( / 2, n 1) S D t n          D’s have a normal distribution Y es  1 -  2 1 1 2 2 1 2 / 2 1 2 p (1 p ) p (1 p ) (p p ) z n n            n1p1 10 and n1(1- p1)  10 and n2p2  10 and n2(1- p2)  10