Descriptive statistics, despite their simplicity, are quite powerful tools. These short ratios summarize any given data by central trend analysis or data distribution analysis (Logan, 2021). This approach allows one to obtain general information without the need for detailed analysis quickly. This is especially useful in cases where the volume of examined data is substantial, and the employee does not have time to explore the entire array independently. The use of middle-level measures allows one to get the average value of the array parameters quickly. In the context of my work, it is not necessary to know all the student’s grades in most cases. However, the average grade or GPA can be instrumental in making the final decision. When using such methods, some details are lost, but the employee can assess the collective properties of the elements under study.
Approximately the exact application of these methods can be found in everyday life. Every day, we face a massive amount of data thanks to modern technology and the Internet. However, processing this amount of data can be extremely difficult in many cases. In such cases, one of the variations of descriptive statistics can come to the rescue. So, for example, it is entirely unnecessary to know all the prices for the same product. You just need to calculate the average price to get a general idea of the cost, which, in turn, will allow you to calculate the monthly budget.
Thus, from my point of view, in everyday life, these methods will be used by me more often than at work. I do not constantly face large amounts of data at my workplace. On the other hand, every day, like any other person, I have to analyze many things, processing quite large flows of information. Descriptive statistics are essential to make this processing easier.
I learned several new uses of descriptive statistics through reading this text, such as compiling spreadsheets of daily duties and activities. This practice can be beneficial if used consistently. Indeed, any data that has categories can be described using similar methods. In addition, the graphical presentation of information is convenient and makes it easier to perceive the information. Are there any other examples of how these statistical methods are used in everyday life? Considering that I agree with your opinion regarding the more frequent use of descriptive statistics in everyday life, it would be extremely interesting for me to listen. However, I do not entirely agree with the amount of data, which, according to the text, constitutes a “statistical amount.” Although 50 days is a rather significant period, in the context of any essential points, such a statistical sample may be insufficient. Therefore, I would like to supplement this example with a proposal to estimate the required amount of data for each category.
Thanks to this post, I looked at descriptive statistics from the business side and the requirements that this area provides for statistics. First of all, this post emphasizes the need to organize and provide interpreted information from the entire volume of data. Given the number of different meanings in the business area, descriptive statistics seems to be the most logical for visualization and interpretation. However, I agree that in my personal life, these statistics are much more critical. It is unnecessary to constantly use these methods in all spheres of professional activity while everyday people, if not compile themselves, then evaluate other people’s statistics. The situation with COVID-19 is a vivid example because, from the entire volume of information regarding the pandemic, experts select the most important one and present it to ordinary people as guidance. Nevertheless, I would like to note that you can take a more active position in this issue: do not wait until the results of statistics affect your life, but use them to change your life on your own.
Reference
Logan, M. (2021). Descriptive statistics.