'Case 302 July in Multiplex\r'

'Case 302From this case, in that respect be two eccentrics of demerits, which the crime syndicate stooge make. A Type I wrongdoing is referred to as a â€Å" unreasonable positive. ” A Type I error would be made when the null hypothesis is standed when it should be accepted. This error may lapse if the consortium defends any wooing against them if they are using 6% (6/ degree centigrade) as their examine result. The results of the type size of 100 batch indicate that the percentage range is from 1. 35% to 10. 65%. The test results can be high than 10%, plainly in reality it is lower.\r\nTherefore, if the consortium defends any lawsuit against them it is potential that a Type I actus reus can be made. The second type of error is a Type II Error, which is also known as â€Å"false negative. ” A Type II error would be made when the alternative hypothesis is rejected when it should be accepted. For this to occur, the consortium must(prenominal) make a de cision to come down the case when the survey result shows a lower percentage than 10% but in reality it is actually higher than 10%. The only error the consortium should make is a Type II error because the alternative hypothesis was rejected.\r\nAs previously stated, using a sample size of 100 shows that we would not reject the null hypothesis, in other words, this would compressed to settle with Tommy. If we did not create a second hypothesis test using a sample size of ccc, we would not hand over defended against Tommy in court and a Type II error would sustain been made. Size of simple| Defend lawsuit| Settlement| 100| Type II Error| Right decision| three hundred| Right decision| Type I Error| Table 1 We have proven that 94% of the surveyed moviegoers indicated that they are conform to that theater play commercials to begin with movie.\r\n merely 6% of the moviegoers opposed to watch commercials before movie. This statistical analysis validates that the consortium should test to defend any lawsuit Tommy or any other unhappy moviegoer files. In this situation, a Type II error would have been made if we unyielding to base our analysis only on a sample size of 100. A larger sample size continuously depicts a more accurate display. statistical Analysis H0 = 10% H1 < 10% inaugural Same Size N: 100 (sample size) p? : 6/100 = . 06 presumption Interval .06 1. 96 = . 0135 †. 1065Test StatisticZ= = -1. 33, from Standard common dispersion table => P-value = . 0918 P-value > ( important) .0918 > . 05 Since P-value (. 0918) is greater than important (. 05), we fail to reject the null hypothesis. second Sample Size N: 300 p? : 18/300 = . 06 reliance Interval .06 1. 96 = . 0331 †. 0869 Test Statistic Z= = -2. 31 from Standard Normal Distribution table => P-value = . 0104 P-value < alpha .0104 < . 05 Since P-value (. 0107) is less than alpha (. 05), we reject the null hypothesis\r\n'