In the past, the mean runing ime for a certain type of flshight attery has been 7.9 hours. The manufecturer has introduced a change in the production method which he hopes has increased the mean running time. The mean running time for a random sample of 40 light bulbs was 8.1 hours. Do the data provide sufient evidence to condude that the mean running time of al light bulbs, u, has increased from the previous mean of 7.9 hours? Perform the appropriate hypothesis test using a signficance level of 0.05. Assume that o = 0.5 hours. Ho : µ= 8.1 hours Hị : µ > 8.1 hours a = 0.05 OZ=2.62 P-value = 0.0044 Reject H, . At the 5% significance level, the data provide sufficient evidence to conclude that the mean running time of all light bulbs, µ, has increased from the previous mean of 8.1 hours. Ho : u = 7.9 hours H1: u> 7.9 hours a = 0.0S z- 2.62 P-value - 0.0044 Reject Ħ, . At the 5% significance level, the data provide sufficient evidence to conclude that the mean running time of all light bulbs, µ, has increased from the previous mean of 7.9 hours. Ho : µ=7.9 hours Hị : µ> 7.9 hours a= 0.05 Oz=2.53 P-value - 0.0057 Reject Ħ. . At the 5% significance level, the data provide sufficient evidence to conclude that the mean running time of all light bulbs, µ, has increased from the previous mean of 7.9 hours. Ho : u = 8.1 hours H : u> 8.1 hours a - 0.05 = 2.53 P-value - 0.0057 Reject Ho - At the 5% significance level, the data provide sufficient evidence to conclude that the mean running time of all light bulbs, , has increased from the previou s mean of 8.1 hours.

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Types of Bias

Statistics is the study of data collection, organization, analysis, interpretation, and presentation. Statistical bias is a characteristic of a statistical technique or its findings in which the expected value deviates from the actual root quantitative parameter being estimated. According to the actual definition of bias, it refers to the tendency of a statistic to overestimate or underestimate a parameter.