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As an underwriter, I am constantly working with large amounts of data.  Whenever I receive data from an outside source, the data is always just messy.  I have almost zero patience with sloppy data, and I will never just sit down and pick through it.  I will always instantly put the data into a pivot table.  The pivot table feature Excel offers is such a lifesaver for me.  Being able to take thousands of lines of data and put it into a chart form that you can manipulate is extremely helpful.  Not only does it just help me with my daily responsibilities, but it also can assist with presenting data.  There are times when I need to present data to management, and I can't just hand them a file with numbers all over the place.  The data will need to be organized and easy to understand.  The best way to accomplish that is to use some form of a table, chart, or graph.  “Sales managers, stock analysts, hospital administrators, and other busy executives often need a quick picture of the distributions of sales, stock prices, or hospital costs” (Lind, Marchal, & Wathen, 2017, pg. 32).  As pointed out in this quote, often a quick data reference is needed for many different jobs, and the best way to accomplish that is to utilize some form of graphical analysis.

Quantitative analysis is the process of turning raw data into useable information, which is very similar to graphical analysis, which converts data into a chart, graph, or table.  So, the graphical analysis will put the data into an illustration that is very useful for many different situations, such as giving a presentation.  

            I found the article on misleading graphs to be very interesting.  I know data can be manipulated to tell a one-sided story, I'm guilty of doing this myself.  When I'm presenting a renewal to an account manager, to numbers will always tell the story I want them too.  What was interesting was the use of graphs in the same fashion.  I have never done that before, but looking at the example in the article and reading through the explanation of misleading graphs, it's clear to see it's possible.

            “Errors using inadequate data are much less than those using no data at all.”—Charles Babbage.  I like this quote because it is something I sale to the sales team regularly.  On the new business side where it can be tough to get all the information I need, I will constantly say to the sales team, "the more data you get me, the better the price will be."  Which to be honest is not 100% of the time accurate, but it gets my point across that I want more data.

Lind, D. A., Marchal, W. G., & Wathen, S. A. (2017). Statistical techniques in business and economics (17th ed.). Retrieved from http://connect.mheducation.com/class/

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Two main types of analysis are used to illustrate knowledge to users. First is a quantitative analysis done on numerical data to represent the values and the other is graphical analysis in which figures like a pie chart, bar chart, and pictograph are used (D'Agostlno, 2017). Now there are many advantages of using graphical analysis as it can lead to an easier understanding of data. Moreover, the analysis is sometimes represented to end-user who is a common man sometimes, so he can understand the concept better with the usage of graphical analysis. Also, the data becomes visually more appealing which can attract the user and make the presentation more attractive. Graphical analysis is also used to provide a summary of information which can be easy for others to understand. The graphical analysis technique is really important in research as it provides a summary instead of details. The users who use graphical tools should choose the type of graph very precisely as it right graph can lead to better representation of information. Bar graphs are used to compare two information whereas the line graph is used to represent the trends (Lind et al., 2012). These differences should be kept in mind while selecting one graph.

Reference

Lind, D. A., Marchal, W. G., & Wathen, S. A. (2012). Statistical techniques in business & economics. New York, NY: McGraw-Hill/Irwin,

D'Agostlno, R. B. (2017). Graphical analysis. In Goodness-of-Fit-Techniques (pp. 7-62). Routledge.