Skip to content

Explore Courses | Elder Research | Contact | LMS Login

Statistics.com
  • Curriculum
    • Curriculum
    • About Us
    • Testimonials
    • Management Team
    • Faculty Search
    • Teach With Us
    • Credit & Credentialing
  • Courses
    • Explore Courses
    • Course Calendar
    • About Our Courses
    • Course Tour
    • Test Yourself!
  • Mastery Series
    • Mastery Series Program
    • Bayesian Statistics
    • Business Analytics
    • Healthcare Analytics
    • Marketing Analytics
    • Operations Research
    • Predictive Analytics
    • Python for Analytics
    • R Programming
    • Rasch & IRT
    • Spatial Statistics
    • Statistical Modeling
    • Survey Statistics
    • Text Mining and Analytics
  • Certificates
    • Certificate Program
    • Analytics for Data Science
    • Biostatistics
    • Programming for Data Science – R (Novice)
    • Programming for Data Science – R (Experienced)
    • Programming for Data Science – Python (Novice)
    • Programming for Data Science – Python (Experienced)
    • Social Science
  • Degrees
    • Degree Programs
    • Computational Data Analytics Certificate of Graduate Study from Rowan University
    • Health Data Management Certificate of Graduate Study from Rowan University
    • Data Science Analytics Master’s Degree from Thomas Edison State University (TESU)
    • Data Science Analytics Bachelor’s Degree – TESU
    • Mathematics with Predictive Modeling Emphasis BS from Bellevue University
  • Enterprise
    • Organizations
    • Higher Education
  • Resources
    • Blog
    • FAQs & Knowledge Base
    • Glossary
    • Site Map
    • Statistical Symbols
    • Weekly Brief Newsletter Signup
    • Word of the Week
Menu Close
  • Curriculum
    • Curriculum
    • About Us
    • Testimonials
    • Management Team
    • Faculty Search
    • Teach With Us
    • Credit & Credentialing
  • Courses
    • Explore Courses
    • Course Calendar
    • About Our Courses
    • Course Tour
    • Test Yourself!
  • Mastery Series
    • Mastery Series Program
    • Bayesian Statistics
    • Business Analytics
    • Healthcare Analytics
    • Marketing Analytics
    • Operations Research
    • Predictive Analytics
    • Python for Analytics
    • R Programming
    • Rasch & IRT
    • Spatial Statistics
    • Statistical Modeling
    • Survey Statistics
    • Text Mining and Analytics
  • Certificates
    • Certificate Program
    • Analytics for Data Science
    • Biostatistics
    • Programming for Data Science – R (Novice)
    • Programming for Data Science – R (Experienced)
    • Programming for Data Science – Python (Novice)
    • Programming for Data Science – Python (Experienced)
    • Social Science
  • Degrees
    • Degree Programs
    • Computational Data Analytics Certificate of Graduate Study from Rowan University
    • Health Data Management Certificate of Graduate Study from Rowan University
    • Data Science Analytics Master’s Degree from Thomas Edison State University (TESU)
    • Data Science Analytics Bachelor’s Degree – TESU
    • Mathematics with Predictive Modeling Emphasis BS from Bellevue University
  • Enterprise
    • Organizations
    • Higher Education
  • Resources
    • Blog
    • FAQs & Knowledge Base
    • Glossary
    • Site Map
    • Statistical Symbols
    • Weekly Brief Newsletter Signup
    • Word of the Week

Blog

Home » Blog » Analytics » Things are Getting Better

Things are Getting Better

  • January 17, 2019
  • , 10:28 pm

In the visualization below, which line do you think represents the UN’s forecast for the number of children in the world in the year 2100?

Hans Rosling, in his book Factfulness, presents this chart and notes that in a sample of Norwegian teachers, only 9% correctly identified the correct answer. Rosling, who died two years ago next month, notes that better results would be obtained by guessing randomly – chimpanzees guess the correct answer 33% of the time. The correct answer is C, and two factors are at work in leading people astray.

  • An extrapolation of previous trends would lead one to guess A or B.

  • More important, what people have read and seen in the news over many years has conditioned them to think in terms of the population problem, i.e. rapid population growth in poor countries that will strain the world’s resources and degrade the environment.

In 1968, when Paul Ehrlich published his book The Population Bomb, an unsustainable worldwide population explosion was the consensus view – fertility rates in China and India were about 6. The big story since then has been the drop in birth rates, India and China now hover just at and below replacement rates (which is about 2.3 worldwide).

So the big story here is population stability, no longer population bomb.[1] And, more broadly, all along the story has been that the world’s condition has been improving. Julian Simon (who was a pioneer in resampling methods in statistics) is often regarded as the original apostle of this optimist school. His book The Ultimate Resource set out the thesis that pessimistic or alarmist views are often based on small samples of data (typically time series) that come to our attention because they suggest something alarming. Simon, who also died in February (21 years ago) took various alarms that had been raised (running out of oil, using up farmland) and showed how, when viewed in the context of longer-term trends, the alarm in question was a blip. Just as important, he viewed these alarms in terms of their real meaning to people. The relevant measure of oil scarcity, for example, is not how much oil we think lies beneath the ground, but rather how difficult it is for ordinary people to obtain fuel – in other words, its price and availability.

But, compared to bomb or explosion, the stability story does not sell newspapers or generate re-tweets. The population stabilization story, and the dramatic decline in the fertility rate that lies behind it, is, in fact, a huge story for the planet, but it is a positive one[1], and positive stories are a harder news sell. The human attraction to bad news is related to what psychologists call loss aversion. Daniel Kahneman (in Thinking Fast and Slow) describes how the human tendency to give priority to bad news over good news is rooted deep in human evolutionary history. The ability to quickly recognize and deal with threats and predators contributed to survival in early humans; focusing on good news did not. Images depicting faces of alarm or terror were shown to subjects for 2/100th of a second – too short a period to register cognitively. Nonetheless, the brain’s amygdala, a super-fast neural channel that feeds directly into emotions, showed an intense response to the images, which the subject did not later remember or recognize. Images of happiness do not get this express pathway to the emotions – they must be filtered by the brain’s cognitive processes.

Ironically, images and visualization have played a key role recently in propelling the “optimistic†perspective that Simon pioneered with The Ultimate Resource. Hans Rosling became famous for his web-based dynamic visualizations that dramatically show the improvement of the world on a variety of metrics over time. These interactive visualizations of country conditions can depict five variables at once using the two axes of a scatterplot, the size of markers (population), the color of markers (region) and the movement of markers as you watch (time). Check them out at www.gapminder.org, and learn more about these techniques using Tableau in our course Interactive Data Visualization.

[1] Actually the story may ultimately be population decline, rather than population stability. In prosperous areas like Japan, North America and Europe the fertility rate is already below the replacement rate. The precipitous fertility declines of China and India, along with those countries’ march to prosperity, portend a world population that will ultimately start declining. For now, we can rest comfortably in the world economy’s ability to bring under-employed people into higher levels of capability and productivity. That, plus the ability for robots and machine learning to take over some of the more routine tasks, will at least assure our future well beyond the lifetime of the readers of this article.

Subscribe to the Blog

You have Successfully Subscribed!

Categories

Recent Posts

  • Dec 14: Statistics in Practice December 11, 2020
  • PUZZLE OF THE WEEK – School in the Pandemic December 11, 2020
  • From Kaggle to Cancel: The Culture of AI December 11, 2020

About Statistics.com

Statistics.com offers academic and professional education in statistics, analytics, and data science at beginner, intermediate, and advanced levels of instruction. Statistics.com is a part of Elder Research, a data science consultancy with 25 years of experience in data analytics.

Latest Blogs

  • Dec 14: Statistics in Practice
    December 11, 2020/
    0 Comments
  • PUZZLE OF THE WEEK – School in the Pandemic
    December 11, 2020/
    0 Comments
  • From Kaggle to Cancel: The Culture of AI
    December 11, 2020/
    0 Comments

Social Networks

Linkedin
Twitter
Facebook
Youtube

Contact

The Institute for Statistics Education
4075 Wilson Blvd, 8th Floor
Arlington, VA 22203
(571) 281-8817

ourcourses@statistics.com

© Copyright 2021 - Statistics.com, LLC | All Rights Reserved | Privacy Policy | Terms of Use

By continuing to use this website, you consent to the use of cookies in accordance with our Cookie Policy.

Accept