For this discussion, select a statistical finding that represents a “mutant statistic.” How do you think this all came about?

1 Initial Discussion post and 1 reply to my classmate – 2 Discussions Total

Instructions

1- Please, read chapter 3 of Damned Lies and Statistics (Pages 62-95) and answer the following question in (400 words)

2 – In this chapter, the author discusses “mutant statistics” and how they develop. For this discussion, select a statistical finding that represents a “mutant statistic.” How do you think this all came about?

3- Reply to to Christopher’s response to this question in 300 words.

Christopher’s discussion post:

In chapter 3 of Damned Lies and Statistics, the author Joel Best discusses the topic of “mutant statistics.” Mutant statistics are “distorted versions of the original figures” (Best, 2012). This means that the person attempting to use numbers and calculations in a statistic misunderstand/misinterpret their meanings. In other words, this is called “innumeracy” (Best, 2012). Joel Best also states that those that innumerate statistics, generally misunderstand how the problem has been defined and measured, and what type of sampling was used. Unfortunately, these mutant statistics are very common in society today. Let’s be honest, there are many people out there that would believe any statistic that they see, without giving it any further thought. We all have most likely fallen victim to this before, myself included, which just proves even further how big of an issue mutant statistics and innumeracy really are in the world today.

Furthermore, for the purpose of this discussion, I will talk about a statistical finding that I found which I believe best represents a mutant statistic. I decided to choose a BJS study on Hate Crime Victimization from 2004-2015. According to the study, a hate crime is defined as “crimes that manifest evidence of prejudice based on race, gender, or gender identity, religion, disability, sexual orientation, or ethnicity” (Langton and Masucci, 2017). One of the findings of this study was that U.S. residents experienced an average of 250,000 hate crime victimizations from 2004-2015 (Langton and Masucci, 2017). The question I have, is how is this data collected on hate crimes, or how is a hate crime even determined?

It seems like this type of crime is a judgement call by a police officer. As human beings, we all see things differently than one another. One police officer may think something could be considered a hate crime, whereas another officer could think the complete opposite. Bias can play a very big role here. Joel Best describes this very well in the text. Context matters in this regard and let’s take a southern community for example. It is no secret that states in the south have been traditionally more racist than any other states across the country. Therefore, police officers may have a bias towards the race of the criminal/victim involved, thus completely skewing the information gained in this study. The same could be said for religion. The majority of people in the United States are Christians, therefore it could be assumed that there is more bias towards these people than someone that is Muslim, for instance. Therefore, a police officer may/ may not not consider something a hate crime if an act is committed by a Christian against a Muslim. Although that is unfortunate, it is just the harsh reality of the world we live in today. Hopefully moving forward, racial injustice will not be as big of an issue, as it currently is.

In addition, the report further shows that its statistics may be mutant. It stated that “1 in 6 hate crime victimizations were thought to be motivated by bias against a victim’s religion (17%) or disability (16%)” (Langton and Masucci, 2017). The key word here to me is “thought.” The crime may not have been a hate crime at all, someone just “thought” that it was, which shows that this might not be reliable data. This goes back to my statement earlier, that police officers and victims for that matter, all think differently to what constitutes a hate crime, and this statement in the report proves just that. Another statistic that was listed stated that “about a third of victims believed that they were targeted because of their ethnicity (35%) or gender (29%) (Langton and Masucci, 2017). Again, it is not certain that these were actually hate crimes that were committed, it is just people’s personal beliefs without any further recollection stated in the study. Anyone could claim that they were targeted because of their ethnicity or gender without giving any further information, which makes me question this study even more.

The last thing that caught my eye in this study was that individual states were not listed at all. The information listed were hate crimes committed by region in the United States, like the South, West, Northeast, and Midwest (Langton and Masucci, 2017). This makes me wonder if every state even participated in this study. It is likely that some of the states did not participate, as Joel Best stated that in the past, not all states and law enforcement agencies participated in reports like this one (Best, 2012). Again, this makes me question the validity of data presented, and that these statistics appear mutant to me upon further investigation. The topic of hate crimes is just too complicated to be statistically evaluated upon, because of all the reasons I gave in this discussion.

When it all comes down to it, I believe mutant statistics are created because of people’s personal views. They want to persuade or convince other people to agree with them on a certain topic that was not very possible, prior to the mutant statistic that they made. I feel as if many businesses that are competing against each other do this especially, to make one look better than the other, like Verizon and AT&T for example. Also, I believe that many political figures make these mutant statistics as well, so that they can again, be depicted as better than the other candidate that they are running against. As a society, we truly need to investigate these statistics better, instead of being so narrow minded and believing whatever we see. I feel that whenever there are numbers and/or percentages listed, people automatically think that what they are looking at is legit. It is imperative that we do not have that preconceived notion anymore and I am glad that I was able to learn this through reading the textbook for this course.

References

Best, J. (2012). Damned Lies and Statistics. Berkeley, CA: The University of California Press.

Langton, L., Masucci, M. (2017). Hate Crime Victimization, 2004-2015. Retrieved September 16, 2018 from https://www.bjs.gov/content/pub/pdf/hcv0415.pdf

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