Three Kinds of Lies: Lies, Damned Lies, & Statistics
My title comes from a review from New York Times journalist Manjit Kumar quoting Mark Twain who wrote, “There are three kinds of lies: lies, damned lies and statistics.” Actually, Mark Twain was apparently quoting 19th century British Prime Minister, Benjamin Disraeli, though the true origins of the quote are truly unknown. I suppose one could argue that quotes ought to be minted as the fourth kind of lie, which is problematic for a growing segment of our populations that gets its news from Instagram. In the end, Tom and Dave Chivers’ book How to Read Numbers tactfully and humorously eroded what little remaining faith I had in myself and humanity as a whole.
Of course, I write hyperbolically in part to ease the discomfort this book created – an emotional response to a book about statistics is not an experience I planned on ever having. My discomfort lies in the dystopian society we have collectively cultivated centered on bias. Whether it is the ethnocentric bias of whiteness, which measures normality based on distance from its own perspective, or the bias that white-centered institutions adopt to prefer and promote people of color in order to uphold white supremacy. Statistical bias is a subset of bias, which is a subset of prejudice. We all have prejudices, but the most dangerous prejudices are those which come from places of power. For example, if a poor person is bias toward rich people, the poor person may throw a rock at a rich person’s head causing serious injury. However, if a rich person is biased toward poor people, the rich person may use his wealth and influence to enact policy, limiting access to necessary resources, which poor people need to survive. Furthermore, if a poor person throws a rock a rich person (or any person for that matter) they will likely be charged with assault. However, if a rich person limits poor people’s access to resources, he will likely be rewarded socially and monetarily. This is the basis of capitalism.
It is my persuasion that capitalism is a subset of post-Constantinian Western Christianity, and they are at least inextricably intertwined. So I am sitting with the question, what theological biases/heuristics remain operative within institutionalize churches/educational systems to maintain exclusivity and limit access? How are hermeneutics agreed upon through confirmation bias, or moral stances solidified through what Tom Chivers refers to as the survivorship bias? Theological reflection must include awareness of possible sample bias within homogenous faith communities. For example, do denominations base their stance on homosexuality because of divine decree, or do they based this on prior-held beliefs of the majority, a prime example of a small and biased sample size? Do religious institutions exclude, in one way or another, LGBTQ individuals based on the six bible verses that vaguely address this issue, or has the fruit of such exclusive and harmful doctrine been held up to the light of quantitative research such as the National Survey on LGBTQ Youth Mental Health 2019, which had a sample size of 35,000 American youth.
Ultimately, numbers seem to have power over our narratives. Take for example the commonly quote statistic that 50 percent of all marriages end in divorce. Jessica Shrader wrote for Psychology Today an article title Do Half of All Marriages Really End in Divorce?. In it she writes, “The truth is, the average couple getting married today has more like a 75 percent chance of staying married […] For some, the chance of a divorce is very slim, while for others, the chance of divorce is actually greater than 50 percent—for example, higher-order marriages have a higher divorce rates than we once attributed to all marriages. In other words, if you are entering into a second or third marriage, you face an approximately 75 percent chance of getting divorced, or possibly higher.”  This highly quoted and quippy stat of 50 percent does not take into consideration marriage rank, thus inflating the statistic, making it more shocking and supporting a narrative that is not full true.
Finally, I am considering how statistical bias upholds and legitimizes the web of heuristics that enable System 1 thinking. Regardless of political or theological persuasion, wisdom requires that we shift our gaze to that which we cannot or do not want to see. The philosophy of civil discourse attempts to do this, but in practice often fails to acknowledge inequity and power-differential. There is a certain self-accountability to own our perspective, but also to peek behind the curtain to see what is hidden off stage by our statisticalized narratives.
- Manjit Kumar. (April 10, 2021 Saturday). Wrestling with the damned lies; This is a timely guide to understanding the numbers in the news,. The Times (London). https://advance.lexis.com/api/document?collection=news&id=urn:contentItem:62DD-BGD1-JCBW-N3R4-00000-00&context=1516831
8 responses to “Three Kinds of Lies: Lies, Damned Lies, & Statistics”
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Michael, your paragraph on the marriage statistics gave me the same feeling I had after inspectional reading this book, namely, I’m leery of any numbers at this point! I appreciate that you connected heuristics to this book and how our biases can lead to manipulation of the numbers. I do wonder how any of us can achieve true objectivity? By the way, great title as I used Twain’s quote too.
Yes exactly! I’m thinking objectivity may be the most subjective of pursuits… If numbers can be seen from so many angles, I’m curious about our doctrine which is often based on narrowly defined interpretation. How is institutionalized religion impacting, positively and negatively, people who are outside its small sample and homogenous segment of the population.
Also, how wild we both chose Twain quotes…
Wow, Michael, there is a LOT to chew on in this post! Again, we really need that front porch, some nice chairs, a good beer, and perhaps a cigar to chat! I enjoyed hearing your struggle with numbers and the many ways in which we have use them for our own gain (even at the cost of others). Lots to consider. Thanks!
Michael – what a thoughtful and powerful post. As an employee at a higher-education institution, I often sit and wrestle with the same question as you regarding the systems in play that limit access to certain student populations. I work at a Minority-Serving Institution (MSI) and Hispanic-Serving Institution (HSI) and yet the majority of those in administrative roles for the university across the various houses do not reflect the diversity of our population as a whole. I was in a organizational health committee meeting months back and encouraged that we invite more employees in order to represent the diversity we have because I’m convinced that we can’t lead organizational health without an accurate representation and a variety of voices contributing to the conversation. In the same meeting we were reviewing data from a recent workplace survey. Only 5 employees that identified as black completed it and I was surprised that others in the room said the same size was too small to make a statistical impact on the results — I ended up pushing that we be provided the actual numbers of employees based on their ethnic identity to ensure that we know the correct denominators. While 5 may be a ‘small number’ on paper, it’s actually a significant number given the total number of black employees we have.
Curious to see how you’ve seen this play out in higher-ed yourself.
Michael: Your example of divorce statistics is an excellent reason why statistics are more complicated than they seem. The use of a single percentage to describe an event at first glance can appear to be so simple. Surely there could be nothing more to it, can thee? But with just a little digging a more complicated picture emerges immediately. This book help me to be quicker to have a heathy dose of skepticism when reading an article that includes numbers to reveal a truth. It is never so simple.
Michael, first….are you really speaking hyperbolically? 🙂
I appreciate your thoughts on bias of power. Another aspect of power was quoted (statistically speaking) by Deep Throat…”Follow the money”.
You ask, “For example, do denominations base their stance on homosexuality because of divine decree, or do they based this on prior-held beliefs of the majority, a prime example of a small and biased sample size?” I think that the answer is sort of both and more. Humans also build walls to keep others out because of fear/anxiety. It’s also shaped by how individuals and communities understand who God is and the way God relates to them and the created world.
Can you say more about what your thoughts are around this, “I am considering how statistical bias upholds and legitimizes the web of heuristics that enable System 1 thinking” ?
Great questions! You are really chewing on all sorts of content. You really challenged my vocabulary comprehension as well.
I find your struggle with the inequality and power-differential fascinating. I struggle with that discussion as well, particularly in light of some of the parables. Like the one where everyone gets paid the same amount regardless of when they started. Or when Jesus says that you will always have the poor among you. Yet there is always the possibility of an abundant life in Jesus. I am conflicted.
Thank you, Michael, for your thought-provoking post. The way you unpacked bias as it relates to prejudice and tied that to the wrestlings around power, ethnically/culturally who has been in the ‘driver’s seat’ of key historical and present-day dynamics over the past 500-1700 years or so, and economics has the makings of a theology of ethics praxis book I would love to read!
You write: “My discomfort lies in the dystopian society we have collectively cultivated centered on bias.” I’m curious if you have yet experienced a sense of invitation around this discomfort as you hold it in the Light?