Journal: Understanding Confidence Intervals
In sections 3.1 and 3.2 of your WileyPLUS textbook, you will learn about confidence intervals. Confidence intervals are often misinterpreted and commonly confused with the probability that something is likely to happen. In this journal, you have the opportunity to explore your understanding of these concepts; you will discuss how calculating a confidence interval is similar to or different than gamblingJournal 4-1: Understanding Confidence Intervals
Confidence Interval is a range of values so defined that there is a specified probability that the value of a parameter lies within it. Confidence intervals in statistics refer to the chance or probability that a result will fall within that estimated value. The most often used in statistics is the 95% confidence interval. A confidence interval gives us information regarding a population parameter. It is an interval estimate, computed from a sample, that has a predetermined chance of capturing the value of the population parameter. Gambling mathematics is a collection of probability applications in games of chance. Gambling mathematics is similar to confidence interval because they both try to conclude a probability or chance of an event. In gambling, there are numerous categories of events which are all predefined. Once again, both confidence interval and gambling are similar in the fact that they are both from a predetermined or predefined value of an event. The difference I perceive between the confidence interval and gambling mathematics is in the computation or equation of the event. I personally am not very good at any form of gambling and would never have even thought to utilize a confidence interval or gambling mathematics to form a probability to help my chances in winning. In my profession as a nurse, we utilize confidence interval when trying to find the probability of a patient getting the flu, or a certain type of infection. There are so many aspects in nursing where confidence interval plays a role.