Case 302 July in Multiplex

Case 302From this case, there are two eccentrics of errors, which the pool open fire refer. A theatrical role I Error is referred to as a fictional positive. A Type I error would be make when the useless hypothesis is corrected when it should be accepted. This error may occur if the consortium defends any typeface against them if they are using 6% (6/100) as their examine result. The results of the standard size of 100 people indicate that the percentage meander is from 1. 35% to 10. 65%. The test results can be higher than 10%, but truly it is lower.Therefore, if the consortium defends any casing against them it is possible that a Type I Error can be made. The second type of error is a Type II Error, which is also known as 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 make a termination to settle 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.As previously stated, using a sample size of 100 shows that we would not reject the null hypothesis, in other words, this would mean to settle with Tommy. If we did not crap a second hypothesis test using a sample size of 300, we would not have defended against Tommy in court and a Type II error would have been made. size of it of simple Defend lawsuit Settlement 100 Type II Error Right decision 300 Right decision Type I Error tabularise 1 We have proven that 94% of the surveyed moviegoers indicated that they are satisfied that champaign play commercials forwards movie.Only 6% of the moviegoers opposed to watch commercials before movie. This statistical analysis validates that the consortium should seek to defend any lawsuit Tommy or any other unhappy moviegoer files. In this situation, a Type II error would have been made if we decided to derriere our analysis only on a sample size of 100. A larger sample size always depicts a more right display. Statistical Analysis H0 = 10% H1 10% 1st Same Size N 100 (sample size) p? 6/100 = . 06 Confidence breakup .06 1. 96 = . 0135 . 1065Test StatisticZ= = -1. 33, from Standard Normal Distribution control board = P-value = . 0918 P-value ( of import) .0918 . 05 Since P-value (. 0918) is greater than alpha (. 05), we fail to reject the null hypothesis. 2nd Sample Size N 300 p? 18/300 = . 06 Confidence 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