Why World Happiness Data Should Make Us Smile

Why World Happiness Data Should Make Us Smile

Can happiness be measured? If so, what do the measurements tell us about the state and trajectory of happiness in the world? Steven Pinker believes that the world is getting better, and happiness is part of that. By sharing world happiness data, he shows that happiness levels are up and that the statistics on mental illness and loneliness look better than we might imagine. Read more to learn why Pinker is optimistic when it comes to world happiness.

Human Rights Statistics: Why There’s a Good Reason for Hope

Human Rights Statistics: Why There’s a Good Reason for Hope

Is there progress in the arena of human rights? Are bigoted attitudes on the decline in the world? In Steven Pinker’s argument that humanity is advancing rather than worsening, he includes some hope-inspiring human rights statistics. He specifically considers racism, sexism, and homophobia to be the biggest contributors to human rights abuses. Keep reading to discover why Pinker believes that we should acknowledge the great advances the world has made in these areas.

Is the World Safe? Possibly More Than You Think

Is the World Safe? Possibly More Than You Think

Is the world safe? Is violent crime getting worse? Are disasters more common and more deadly? In Enlightenment Now, Steven Pinker presents statistics in several areas to support his argument that the world is getting better for humans everywhere. One of those areas is safety, so he looked at data on injuries and deaths. With one exception, he concludes that the world is safer than in the past. Continue reading to get a good picture of the data, according to Pinker.

Probabilistic Thinking: The 3 Forms, Explained

Probabilistic Thinking: The 3 Forms, Explained

Can you train yourself to think in probabilities? How can this mental model help you make better decisions? In The Great Mental Models Volume 1, Shane Parrish and Rhiannon Beaubien explain how estimating probabilities can narrow down decisions. They discuss three types of probabilistic thinking: Bayesian thinking, fat-tailed curves, and asymmetries. Keep reading to learn how probabilistic thinking can help you navigate difficult decisions.

Naked Statistics: Book Review and Commentary

Naked Statistics: Book Review and Commentary

What is Charles Wheelan’s Naked Statistics about? What statistics does Wheelan cover in the book? Statistics help us use data to make sense of the world, and statistical insights help guide modern society, informing medical practices, public and fiscal policy, education initiatives, business and marketing decisions, and so on. But many people find statistics intimidating. In his book Naked Statistics, Charles Wheelan aims to demystify statistics to make them more accessible for non-mathematical audiences. Keep reading for our review of Naked Statistics, including the author’s background and commentary on the book’s approach.

The Common Types of Bias in Statistics

The 25 Cognitive Biases: The Availability Bias

What are the different types of bias in statistics? What are some ways bias can creep into a research project? As individuals and as a society, we rely on scientific research to make informed decisions and to understand the world around us. Therefore, researchers have an ethical obligation to identify and address sources of bias in their research. Statistical bias can make its way into a research project anywhere along the way, from the study’s conception to the research question, the data collection, the statistical analysis, the reporting of findings, and the study’s publication. Keep reading to learn about the

Why Thinking in Probabilities Is Not Intuitive

Why Thinking in Probabilities Is Not Intuitive

Do you take into account probability when making decisions? Why do we make decisions that contradict probabilistic logic? Understanding probability can be especially relevant to our daily lives because we make decisions based on our perception of probability all the time. However, our perception of likely outcomes is often mathematically irrational. This is because thinking in probabilities isn’t intuitive: Most people think in terms of binary categories of “yes,” “no,” and “maybe.” Here’s why we make decisions that contradict probabilistic logic.

What Is Inferential Analysis in Statistics?

What Is Inferential Analysis in Statistics?

What is inferential analysis? What can inferential statistics tell us about data? In simple terms, inferential statistics are a kind of combination of data and probability. Just as probability is never a guarantee of an outcome, there are no definitive answers in inferential statistics. Rather, inferential statistics help us use what we do know to make math-based best guesses about what we want to know. Keep reading for the ultimate guide to inferential statistics.

The Correlation Coefficient: Statistics 101

The Correlation Coefficient: Statistics 101

What is the correlation coefficient in statistics? What can the correlation coefficient tell us about the relationship between two variables? What is the danger in mistaking correlation for causation? A figure called the correlation coefficient quantifies the strength and direction of the relationship between two variables. A common mistake in statistics is equating correlation with causation. It can be tempting to extrapolate beyond a correlation coefficient, but that will lead to causal conclusions that correlation can’t support. In this article, we’ll break down the concept of statistical correlation and explain why correlation does not equal causation.

Healthy-User Bias in Medical Research

Healthy-User Bias in Medical Research

What is healthy-user bias? How can we isolate whether an intervention actually accounts for differences between individuals? Healthy-user bias occurs in studies that aim to assess the effect of a certain treatment or intervention. Because the people who choose to partake in such studies tend to be significantly different from their peers, it’s difficult to assess the degree to which the intervention (and not the participants’ characteristics) accounts for the findings.  Keep reading to learn about healthy-user bias and how it affects research findings.