What possible errors can occur at Norchem Drug Testing?
Despite how much reliable testing is in determining contents in different substances, errors might arise thus affecting a resulting outcome. Two possible errors that can occur at Norchem testing company are false positive or False Negative error results. Getting errors in a test is very crucial in regards to consequences faced after the test has been carried out. It is noteworthy to understand that false negative does not present contentious consequences as compared to false positive.
Which type of error is of greater concern to Norchem Drug Testing?
The false Positive error is of great concern at the testing company. Norchem Drug Company has been offered a contract by various law enforcement organizations to carry out tests on samples delivered to them. False positive errors, therefore, receive a thorough and strict testing due to consequences faced after testing. The reason is that false positive error might lead to a wrong individual behind bars, on probation or on administrative sanction, a decision that might have been made on false results and decision making during a test. This is the reason false positive test are subjected to another manual test to ensure that the error is near to zero.
Norchem Drug Testing tries to ensure that the probability of a false positive is near zero. What type of probability is this? In the context of hypothesis testing, what would we call this probability?
Type I error in probability is done to ensure that a certain event is unlikely to happen hence its occurrence is near zero. In statistics and context of hypothesis, it is regarded as a probability with aim of rejecting a null hypothesis that is true. Therefore type I error allows room to subject the test to another alternative hypothesis by assigning the outcome results to chance. In relative probability, the results of type I error are seen as negative in relation to the null hypothesis of a test research.
Give a scenario other than drug testing that is designed to keep the probability of making a Type I error small.
The perfect scenario on making probability of type one error very small would be for example testing the effectiveness of a new polio vaccine on children. The null hypothesis would be that, "the new polio vaccine has no effect on children administered with it." Type one error would be that the polio vaccine has no effect when in a real sense the vaccine has an effect on children. An alternative hypothesis would be created by subjecting the test to a more specific test and assigning results to another chance.
Banerjee, Amitav, UB Chitnis, SL Jadhav, JS Bhawalkar, and S Chaudhury. (2017). "Hypothesis Testing, Type I And Type II Errors."
Keppel, G., & Wickens, T. D. (2004). Simultaneous comparisons and the control of type I errors. Design and analysis: A researchers handbook. 4th ed. Upper Saddle River (NJ): Pearson Prentice Hall. Pp, 111-130.
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