Part 1

256 Chapter 13 Inferential Statistics in Healthcare Dealing with levels of uncertainty in hypothesis testing creates two types of errors: Type I errors and Type II errors. A Type I error occurs when the null hypothesis is rejected, yet it is actually true. A Type II error occurs when the null hypothesis is not rejected, yet it is false. Following are examples of both types of errors. Type I Error According to the National Cancer Institute, a woman's chance of being diagnosed with breast cancer from age 50 through age 59 is 2.38 percent (NCI 2012). With this knowledge, going to see a doctor because of a lump on her breast presents a risk that the doctor will diagnose the patient with breast cancer even if she does not have breast cancer. Consider the following null hypothesis: there is no difference between women diagnosed with breast cancer and women not diagnosed with breast cancer. Rejecting the null hypothesis in this instance would be assuming that the doctor will not diagnose her with breast cancer, as there is a difference between the two populations (women diagnosed with breast cancer and women not diagnosed with breast cancer). However, if she is diagnosed with breast cancer, this would be an example of a Type I error. Simply said, the patient could receive a positive test result when, in fact, she does not have breast cancer. Type II Error A Type I error is controlled by the researcher setting the acceptable error rate. A Type II error is driven by the sample size and the particular test used. Suppose a drug company has developed a new drug for a serious disease and the new drug is effective. If, however, the null hypothesis is not rejected because the drug company selected a level of significance that is too high, the results of the study will have to be described as insignificant and the drug may not receive government approval (Pyrczak 2010, 83). This is an example of a Type II error. When describing the null hypothesis, it is never "accepted." Rather, we say "reject the null hypothesis" or "fail to reject the null hypothesis." Exercise 13.2 Use the following information to provide an example of a Type I and Type II error. A pharmaceutical company tests a promising new medicine designed to lower cholesterol when taken daily. The pharmaceutical company conducts a study to determine the effectiveness of the medication against a placebo. Consider the null hypothesis: there is no difference between the effectiveness of the new medication and the placebo in lowering cholesterol. Type I error: Type II error