QMS 202 Lecture Notes - Lecture 3: Type I And Type Ii Errors, Null Hypothesis, Statistic

• School: Ryerson University
• Department: Quantitative Methods
• Course: QMS 202
• Professor: Nursel Ruzgar

Document Summary

Pop mean: monthly cell phone bill is = in this city. Populatio(cid:374) proportio(cid:374): proportio(cid:374) of adults (cid:449)ith cell pho(cid:374)es is =(cid:1004). (cid:1010)8 i(cid:374) this cit(cid:455) States the claim or hypothesis to be tested =30. Always about a population parameter, not sample statistic. Begin with the assumption the null hypothesis is true (innocent until proven guilty) Refers to the status quo or historical value. Null al(cid:449)a(cid:455)s co(cid:374)tai(cid:374)s a(cid:374) = sig(cid:374) (cid:894)(cid:1095), =, (cid:1096)(cid:895) never used i(cid:374) alter(cid:374)ati(cid:448)e h(cid:455)pothesis. Can only reject or fail to reject. H1 gives the direction of the test (look at the symbol) If h(cid:1004) (cid:1095)(cid:1004). (cid:1009) a(cid:374)d h(cid:1005)>(cid:1004). (cid:1009), the tail is right, reject the (cid:374)ull h(cid:455)pothesis is the test is larger tha(cid:374) the upper critical value. If h(cid:1004)=(cid:1004). (cid:1009) a(cid:374)d h(cid:1005) 0. 5 there are two tails. Reject the null if the test is larger than the upper critical value or smaller than the lower critical value.