Complete Discussion Responses for Research Methods Course, discussion help

Reply to the following classmates posts: (At least 100 words)POST 1:Outliers are data points that seems to be distant from the other points shown in the data. They can be problematic due to having misleading results if one does not become aware of it (outlier detection). As a real life example, using the website called Vast for the listing of used cars. The data listing used in this website is created manually by its users causing it to become a human error. As observed in the blog, Detecting outlier car prices on the web (Levy, 2013), users tend to submit the values in the wrong field. An example used of mistyping tends to occur when the miles of a car are entered incorrectly in an 8yr old vehicle or when an unusual price is entered for an older car. A higher price listing can be seen more reasonable on a 2015 Cadillac luxury edition than in a 1997 Buick limited edition. References:Levy, J. (2013, December 18). Detecting outlier car prices on the web [Web log post].  Retrieved from http://blog.yhathq.com/posts/detecting-outlier-car...POST 2:An outliner is a value that is distant (can be higher or lower) from the other data. There could be multiple reasons that outliners occur such as; measurement error, experimental error, human error, intentionally reporting incorrect data, or a sampling error. The easiest way to detect an outliner is to create a graph. This will give you a visual to be able to properly detect a possible outliner.At my current job we recently had to start tracking our day in 15 minute increments. This is due to the salary regulations changing for those in the human services field. Our company wanted to see how we were spending our time and if it was worth continuing to pay employees salary or start paying them hourly. After all the data was collected it not only showed how many hours weekly employees are working (and how they are using their time), but also outliners to those who were not correctly documenting their time. When data was being put into the spreadsheet it showed some employees were working 35-45 hours a week while a outliners were working 80-90 hours due to incorrect data.