Mean
In determining the mean of a set of data, you are determining the middle of the data set. As Anderson, Sweeney, and Williams (2012) state, the mean is “perhaps the most important measure of location” (p. 88). In determining the mean, you are taking all data sets and adding them together then dividing by the number of data sets. This …show more content…
However, mean can be greatly affected by outliners in the data set. To take these outliners into better consideration we can use median. The median is “the value in the middle when the data are arranged in ascending order” (Anderson, Sweeney, & Williams, 2012, p. 89). By determining the middle value in the data set through this method, outliners are better accounted for. If the data is grades on a test, those that are really high such as 100% or those that are really low such as 20% do not affect the middle value as drastically as it would in the mean. If there are outliners median is the best method to use to determine the middle value. Below is the median value for all four variables. The data in table 2 shows us that the average movie spends 14.5 weeks in 3,114.5 theaters with an opening gross of almost 21 million and total gross of about 64 million dollars. In comparing this data to that of the mean you can clearly see the difference in data for the middle variable. The Median is a more accurate number since it takes into account …show more content…
Each scatter plot tells the individual relationship between it and the total gross. The relationship between total gross and opening gross is very closely related. You can tell by the scatter plot that the graph has a positive linear relationship between the two variables. They are very closely linked. If a movie has a high opening gross it is also going to have a high total gross, the same is true for low opening gross leads to low total gross. The number of theaters a movie is in and total weeks are also directly related to the total gross. However, they are not a solid linear relationship like opening gross. The scatter graphs show more of a curve than a linear line. This tells us that for the lower end of the number of theaters a movie is played in and smaller amount of weeks does not affect the total gross drastically. However, when it is shown in many theaters for longer periods it correlates to a higher total