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3 questions to ask yourself next time you see a graph, chart, or map
Start by reading the title, looking at the labels and checking the caption. If these are not available – be very wary.
Since the days of painting on cave walls, people have been representing information through figures and images.
Nowadays, data visualization experts know that presenting information visually helps people better understand complicated data. The problem is that data visualizations can also leave you with the wrong idea – whether the images are sloppily made or intentionally misleading.
Take for example the bar graph presented at an April 6 press briefing by members of the White House Coronavirus Task Force. It's titled “COVID-19 testing in the U.S." and illustrates almost 2 million coronavirus tests completed up to that point. President Trump used the graph to support his assertion that testing was “going up at a rapid rate." Based on this graphic many viewers likely took away the same conclusion – but it is incorrect.
The graph shows the total cumulative number of tests performed over months, not the number of new tests each day.
When you graph the number of new tests by date, you can see the number of COVID-19 tests performed between March and April did increase through time, but not rapidly. This instance is one of many when important information was not properly understood or well communicated.
Whether they show COVID-19 cases, global warming trends, high-risk tsunami zones, or utility usage, being able to correctly assess and interpret figures allows you to make informed decisions. Unfortunately, not all figures are created equal.
If you can spot a figure's pitfalls you can avoid the bad ones. Consider the following three key questions the next time you see a graph, map or other data visual so you can confidently decide what to do with that new nugget of information.
What is this figure trying to tell me?
Start by reading the title, looking at the labels and checking the caption. If these are not available – be very wary. Labels will be on the horizontal and vertical axes on graphs or in a legend on maps. People often overlook them, but this information is crucial for putting everything you see in the visualization into context.
Look at the units of measure – are they in days or years, Celsius or Fahrenheit, counts, age, or what? Are they evenly spaced along the axis? Many of the recent COVID-19 cumulative case graphs use a logarithmic scale, where the the intervals along the vertical axis are not equally spaced. This creates confusion for people unfamiliar with this format.
A March 12 broadcast of 'The Rachel Maddow Show' included a graph with unlabeled numbers and a tricky horizontal axis.
For instance, a graph from “ The Rachel Maddow Show" on MSNBC, showed coronavirus cases in the United States between Jan. 21 and March 11. The x-axis units on the horizontal are time (in a month-day format) and the y-axis units on the vertical are presumably cumulative case counts, though it does not specify.
The main issue with this graph is that the time periods between consecutive dates are uneven.
In a revised graph, with dates properly spaced through time, and coronavirus diagnoses plotted as a line graph, you can see more clearly what exponential growth in the rate of infection really looks like. It took the first 30 days to add 33 cases, but only the last four to add 584 cases.
What may seem like a slight difference could help people understand how quickly exponential growth can go sky high and maybe change how they perceive the importance of curbing it.
How are color, shape, size and perspective used?
Color plays an important role in how people interpret information. Color choices can make you notice particular patterns or draw your eye to certain aspects of a graphic.
Oregon landslide susceptibility. (Oregon Department of Geology and Mineral Industries)
Consider two maps depicting landslide susceptibility, which are exactly the same except for reversed color schemes. Your eye may be be drawn to darker shades, intuitively seeing those areas as at higher risk. After looking at the legend, which color order do you think best represents the information? By paying attention to how color is used, you can better understand how it influences what stands out to you and what you perceive.
Shape, size and orientation of features can also influence how you interpret a figure.
What industries employ Coloradans? (Hemispheres)
Pie charts, like this one showing employment breakdown for a region, are notoriously difficult to parse. Notice how hard it is to pull out which employment category is highest or how they rank. The pie chart's wedges are not organized by size, there are too many categories (11!), the 3D perspective distorts the wedge sizes, and some wedges are separate from others making size comparisons almost impossible.
A bar chart is a better option for an informative display and helps show which industries people are employed in.
Where do the data come from?
Survey posted on 'Lou Dobbs Tonight,' requesting viewers vote on Twitter about Trump's performance. (Fox Business Network)
The source of data matters in terms of quality and reliability. This is especially true for partisan or politicized data. If the data are collected from a group that isn't a good approximation of the population as a whole, then it may be biased.
For example, on March 18, Fox Business Network host Lou Dobbs polled his audience with the question “How would you grade President Trump's leadership in the nation's fight against the Wuhan Virus?"
Imagine if only Republicans were asked this question and how the results would compare if only Democrats were asked. In this case, respondents were part of a self-selecting group who already chose to watch Dobbs' show. The poll can only tell you about that group's opinions, not people in the U.S. generally, for instance.
Then consider that Dobbs provided only positive responses in his multiple choice options – “superb, great or very good" – and it is clear that this data has a bias.
Spotting bias and improper data collection methods allows you to decide which information is trustworthy.
Think through what you see
During this pandemic, information is emerging hour by hour. Media consumers are inundated with facts, charts, graphs and maps every day. If you can take a moment to ask yourself a few questions about what you see in these data visualizations, you may walk away with a completely different conclusion than you might have had at first glance.
- The Minard Map - "The best statistical graphic ever drawn" - Big Think ›
- Coronavirus: Viral video graph omits crucial information - Big Think ›
Innovation in manufacturing has crawled since the 1950s. That's about to speed up.
Health officials in China reported that a man was infected with bubonic plague, the infectious disease that caused the Black Death.
- The case was reported in the city of Bayannur, which has issued a level-three plague prevention warning.
- Modern antibiotics can effectively treat bubonic plague, which spreads mainly by fleas.
- Chinese health officials are also monitoring a newly discovered type of swine flu that has the potential to develop into a pandemic virus.
Bacteria under microscope
needpix.com<p>Today, bubonic plague can be treated effectively with antibiotics.</p><p style="margin-left: 20px;">"Unlike in the 14th century, we now have an understanding of how this disease is transmitted," Dr. Shanthi Kappagoda, an infectious disease physician at Stanford Health Care, told <a href="https://www.healthline.com/health-news/seriously-dont-worry-about-the-plague#Heres-how-the-plague-spreads" target="_blank">Healthline</a>. "We know how to prevent it — avoid handling sick or dead animals in areas where there is transmission. We are also able to treat patients who are infected with effective antibiotics, and can give antibiotics to people who may have been exposed to the bacteria [and] prevent them [from] getting sick."</p>
This plague patient is displaying a swollen, ruptured inguinal lymph node, or buboe.
Centers for Disease Control and Prevention<p>Still, hundreds of people develop bubonic plague every year. In the U.S., a handful of cases occur annually, particularly in New Mexico, Arizona and Colorado, <a href="https://www.cdc.gov/plague/faq/index.html" target="_blank">where habitats allow the bacteria to spread more easily among wild rodent populations</a>. But these cases are very rare, mainly because you need to be in close contact with rodents in order to get infected. And though plague can spread from human to human, this <a href="https://www.healthline.com/health-news/seriously-dont-worry-about-the-plague#Heres-how-the-plague-spreads" target="_blank">only occurs with pneumonic plague</a>, and transmission is also rare.</p>
A new swine flu in China<p>Last week, researchers in China also reported another public health concern: a new virus that has "all the essential hallmarks" of a pandemic virus.<br></p><p>In a paper published in the <a href="https://www.pnas.org/content/early/2020/06/23/1921186117" target="_blank">Proceedings of the National Academy of Sciences</a>, researchers say the virus was discovered in pigs in China, and it descended from the H1N1 virus, commonly called "swine flu." That virus was able to transmit from human to human, and it killed an estimated 151,700 to 575,400 people worldwide from 2009 to 2010, according to the Centers for Disease Control and Prevention.</p>There's no evidence showing that the new virus can spread from person to person. But the researchers did find that 10 percent of swine workers had been infected by the virus, called G4 reassortant EA H1N1. This level of infectivity raises concerns, because it "greatly enhances the opportunity for virus adaptation in humans and raises concerns for the possible generation of pandemic viruses," the researchers wrote.
So far, 30 student teams have entered the Indy Autonomous Challenge, scheduled for October 2021.
- The Indy Autonomous Challenge will task student teams with developing self-driving software for race cars.
- The competition requires cars to complete 20 laps within 25 minutes, meaning cars would need to average about 110 mph.
- The organizers say they hope to advance the field of driverless cars and "inspire the next generation of STEM talent."
Indy Autonomous Challenge<p>Completing the race in 25 minutes means the cars will need to average about 110 miles per hour. So, while the race may end up being a bit slower than a typical Indy 500 competition, in which winners average speeds of over 160 mph, it's still set to be the fastest autonomous race featuring full-size cars.</p><p style="margin-left: 20px;">"There is no human redundancy there," Matt Peak, managing director for Energy Systems Network, a nonprofit that develops technology for the automation and energy sectors, told the <a href="https://www.post-gazette.com/business/tech-news/2020/06/01/Indy-Autonomous-Challenge-Indy-500-Indianapolis-Motor-Speedway-Ansys-Aptiv-self-driving-cars/stories/202005280137" target="_blank">Pittsburgh Post-Gazette</a>. "Either your car makes this happen or smash into the wall you go."</p>
Illustration of the Indy Autonomous Challenge
Indy Autonomous Challenge<p>The Indy Autonomous Challenge <a href="https://www.indyautonomouschallenge.com/rules" target="_blank">describes</a> itself as a "past-the-post" competition, which "refers to a binary, objective, measurable performance rather than a subjective evaluation, judgement, or recognition."</p><p>This competition design was inspired by the 2004 DARPA Grand Challenge, which tasked teams with developing driverless cars and sending them along a 150-mile route in Southern California for a chance to win $1 million. But that prize went unclaimed, because within a few hours after starting, all the vehicles had suffered some kind of critical failure.</p>
Indianapolis Motor Speedway
Indy Autonomous Challenge<p>One factor that could prevent a similar outcome in the upcoming race is the ability to test-run cars on a virtual racetrack. The simulation software company Ansys Inc. has already developed a model of the Indianapolis Motor Speedway on which teams will test their algorithms as part of a series of qualifying rounds.</p><p style="margin-left: 20px;">"We can create, with physics, multiple real-life scenarios that are reflective of the real world," Ansys President Ajei Gopal told <a href="https://www.wsj.com/articles/autonomous-vehicles-to-race-at-indianapolis-motor-speedway-11595237401?mod=e2tw" target="_blank">The Wall Street Journal</a>. "We can use that to train the AI, so it starts to come up to speed."</p><p>Still, the race could reveal that self-driving cars aren't quite ready to race at speeds of over 110 mph. After all, regular self-driving cars already face enough logistical and technical roadblocks, including <a href="https://www.bbc.com/news/technology-53349313#:~:text=Tesla%20will%20be%20able%20to,no%20driver%20input%2C%20he%20said." target="_blank">crumbling infrastructure, communication issues</a> and the <a href="https://bigthink.com/paul-ratner/would-you-ride-in-a-car-thats-programmed-to-kill-you" target="_self">fateful moral decisions driverless cars will have to make in split seconds</a>.</p>But the Indy Autonomous Challenge <a href="https://static1.squarespace.com/static/5da73021d0636f4ec706fa0a/t/5dc0680c41954d4ef41ec2b2/1572890638793/Indy+Autonomous+Challenge+Ruleset+-+v5NOV2019+%282%29.pdf" target="_blank">says</a> its main goal is to advance the industry, by challenging "students around the world to imagine, invent, and prove a new generation of automated vehicle (AV) software and inspire the next generation of STEM talent."
A new Harvard study finds that the language you use affects patient outcome.
- A study at Harvard's McLean Hospital claims that using the language of chemical imbalances worsens patient outcomes.
- Though psychiatry has largely abandoned DSM categories, professor Joseph E Davis writes that the field continues to strive for a "brain-based diagnostic system."
- Chemical explanations of mental health appear to benefit pharmaceutical companies far more than patients.
Challenging the Chemical Imbalance Theory of Mental Disorders: Robert Whitaker, Journalist<span style="display:block;position:relative;padding-top:56.25%;" class="rm-shortcode" data-rm-shortcode-id="41699c8c2cb2aee9271a36646e0bee7d"><iframe type="lazy-iframe" data-runner-src="https://www.youtube.com/embed/-8BDC7i8Yyw?rel=0" width="100%" height="auto" frameborder="0" scrolling="no" style="position:absolute;top:0;left:0;width:100%;height:100%;"></iframe></span><p>This is a far cry from Howard Rusk's 1947 NY Times editorial calling for mental healt</p><p>h disorders to be treated similarly to physical disease (such as diabetes and cancer). This mindset—not attributable to Rusk alone; he was merely relaying the psychiatric currency of the time—has dominated the field for decades: mental anguish is a genetic and/or chemical-deficiency disorder that must be treated pharmacologically.</p><p>Even as psychiatry untethered from DSM categories, the field still used chemistry to validate its existence. Psychotherapy, arguably the most efficient means for managing much of our anxiety and depression, is time- and labor-intensive. Counseling requires an empathetic and wizened ear to guide the patient to do the work. Ingesting a pill to do that work for you is more seductive, and easier. As Davis writes, even though the industry abandoned the DSM, it continues to strive for a "brain-based diagnostic system." </p><p>That language has infiltrated public consciousness. The team at McLean surveyed 279 patients seeking acute treatment for depression. As they note, the causes of psychological distress have constantly shifted over the millennia: humoral imbalance in the ancient world; spiritual possession in medieval times; early childhood experiences around the time of Freud; maladaptive thought patterns dominant in the latter half of last century. While the team found that psychosocial explanations remain popular, biogenetic explanations (such as the chemical imbalance theory) are becoming more prominent. </p><p>Interestingly, the 80 people Davis interviewed for his book predominantly relied on biogenetic explanations. Instead of doctors diagnosing patients, as you might expect, they increasingly serve to confirm what patients come in suspecting. Patients arrive at medical offices confident in their self-diagnoses. They believe a pill is the best course of treatment, largely because they saw an advertisement or listened to a friend. Doctors too often oblige without further curiosity as to the reasons for their distress. </p>
Image: Illustration Forest / Shutterstock<p>While medicalizing mental health softens the stigma of depression—if a disorder is inheritable, it was never really your fault—it also disempowers the patient. The team at McLean writes,</p><p style="margin-left: 20px;">"More recent studies indicate that participants who are told that their depression is caused by a chemical imbalance or genetic abnormality expect to have depression for a longer period, report more depressive symptoms, and feel they have less control over their negative emotions."</p><p>Davis points out the language used by direct-to-consumer advertising prevalent in America. Doctors, media, and advertising agencies converge around common messages, such as everyday blues is a "real medical condition," everyone is susceptible to clinical depression, and drugs correct underlying somatic conditions that you never consciously control. He continues,</p><p style="margin-left: 20px;">"Your inner life and evaluative stance are of marginal, if any, relevance; counseling or psychotherapy aimed at self-insight would serve little purpose." </p><p>The McLean team discovered a similar phenomenon: patients expect little from psychotherapy and a lot from pills. When depression is treated as the result of an internal and immutable essence instead of environmental conditions, behavioral changes are not expected to make much difference. Chemistry rules the popular imagination.</p>