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Suppose we have an algorithm that can detect whether a particular type of photograph features...

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Suppose we have an algorithm that can detect whether a particular type of photograph features a turtle We seek to demonstrate that our algorightm can out perform the state of the art which has a correct detection rate of 0 7501 We have set our significance level to 0 05 Our hypothesis pair is OHO p 0 7501 HA p 0 7501 OHO p 0 7501 HA p 0 7501 OHO p 0 7501 HA p 0 7501 OHO p 0 7501 HA p 0 7501 OHO p 0 7501 HA p 0 7501 Considering our significance level and using the standard normal model our Critical Region for our test statistic z is closest to Ogreater than or equal to 3 09023 Ogreater than or equal to 1 64485 Ogreater than or equal to 2 57583 Ogreater than or equal to 2 05375 Ogreater than or equal to 2 32635 Suppose we randomly select 423 photographs and our observed sample statistic is p hat 0 85106 Using the standard normal model our observed test statistic z is closest to 04 795974 3 78557 0 3 851125 0 032778 01 427011 Our decision is OWe reject the null hypothesis and conclude our algorithm out performs the state of the art in terms of correct detection rate Owe fail to reject the null hypothesis and do not conclude our algorithm out performs the state of the art in terms of correct detection rate

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