DRAFT: This module has unpublished changes.

Samuel van der Swaagh

Value of Math in Every Day Life

 

            This summer I have grown a greater ability for estimating certain quantities and grasping the meaning of large measurements and numbers. I feel my knowledge of math is important in my daily living because math pertains to all my daily routines and activities. For example, one subconsciously uses math when interpreting star ratings for commercial products, or stores. When one views ratings, he/she determines whether or not the product is good based upon highly organized numerical data (i.e. quantitative data). Even while one views census and survey data, which is categorical or qualitative data, one uses math because whenever a person examines a survey, he/she mentally draws a statistical conclusion. 

During the Summer Bridge Quantitative Reasoning course, I performed a quantitative research project that actively taught me how to collect quantitative data, i.e. data that could be measured and categorized, create a pie or bar graph, and present quantitative analysis of my graph. While I worked on my research for my place and lens, I developed a greater appreciation for graphs because I realized that graphs can influence people’s actions or decisions. The reason for this is that graphs provide people with a visual digestible picture of what the quantitative data means. For example, if a person wants to research the solar system’s largest craters, the person will have a better physical understanding of the data if he/she looks at a graph than if he/she merely reads a chart.

            Thus, it is vitally important to critically understand and examine all aspects or elements of a graph. Often complicated bar graphs can be misleading and overwhelming, and having a strategy for reading graphs can be helpful. In the Summer Bridge Quantitative Reasoning course, it was advised that graph readers start by first analyzing his/her upfront observations.  In other words, the graph reader was encouraged to state what he/she first notices about his/her graph. Such observation could lead to one to recognize whether or not the chosen topics overlap or not. Also, during this first phase of analysis, one could note whether or not the categories are clearly expressed or if the graph title makes sense. In the second phase of analysis, the student must state what he/she finds surprising about the graph. Such elements could include your opinion of whether or not the researcher had created lines of arbitration, or ambiguity. Also in this step, one could also note the trend of the graph, if any. Lastly, in the third phase, the student will attempt to find the missing or confusing components of the graph. Sometimes graphs produced by biased research can have either deceptive or vague scaling. Another bar graph element to keep in mind is the commonly omitted survey total. All these steps are designed to aid a student to become acquainted with his/her graph.

            If I had more time for further quantitative research for my lens and place, which was history, I would have collected data on how people interact with Penn Station’s monuments. It would have been interesting to quantify people’s awareness of Penn Station’s history because the terminal is not as obviously historical as other NYC sites. Also, another reason why I would have chosen such a topic is that I would have had to collect more data. My quantitative research topic was the types of monuments in Penn Station that only amounted to 1 sculpture, 6 murals, 10 photographs, and 1 painting. If I had performed the topic of human interactions, the graph scale would have had increments of hundreds. Not only would the number be huge, but also I would have to break the data into categories of time, race, and medium. Consequently, with such tremendous numbers, I would have had to categorize percentages. In other words, within each category total, I would be forced to calculate percentages.

DRAFT: This module has unpublished changes.