Three years ago today, I predicted: "So, why is the above important? It means to get to herd immunity, something like 82% of people will have to get infected and of those that get infected, 0.4% will die. Then, we can calculate: Population * Percentage of People For Herd Immunity * Death Rate = Deaths … Continue reading Three Years After “Grim News”
Tag: forecasting
CAMALIOT
"Collect data from satellites for scientific research in weather forecasting."-https://www.camaliot.org/ It's an android app that uses your GPS to help collect data to improve navigation and weather forecasting.
Revisiting “A China Prediction”
...there’s going to be a reckoning, and the funny thing is that reckoning is going to begin in China and then eventually spread to the rest of the world. Whether it will happen in close proximity to the end of the COVID-19 pandemic remains to be seen, but there is definitely a short term correction … Continue reading Revisiting “A China Prediction”
The Secret Ingredients of ‘Superforecasting’
"From 2011 to 2015, the US government-funded online initiative pitted the predictive powers of ordinary people against Washington, DC intelligence analysts on the most significant geopolitical questions of the day. Over successive rounds, Tetlock and Mellers identified the very best prognosticators from the 25,000-strong participant pool and shunted them into elite teams. Despite the fact … Continue reading The Secret Ingredients of ‘Superforecasting’
Forecasting in R: Probability Bins for Time-Series Data
This time-series.R script, below, takes a set of historical time series data and does a walk using the forecast period to generate probabilistic outcomes from the data set. Input file is a csv file with two columns (Date, Value) with dates in reverse chronological order and in ISO-8601 format. Like so: 2019-08-06,1.73 2019-08-05,1.75 2019-08-02,1.86 Output … Continue reading Forecasting in R: Probability Bins for Time-Series Data
The Resulting Fallacy Is Ruining Your Decisions – Issue 55: Trust – Nautilus
"In life, it’s usually even more complicated because in most real decisions we haven’t examined the coin. We don’t know if it is a fair coin, if it has two sides with a heads and tails on it and is weighted properly. That’s the hidden information problem. We can’t see everything. We haven’t experienced everything. … Continue reading The Resulting Fallacy Is Ruining Your Decisions – Issue 55: Trust – Nautilus
The Psychology of Prediction · Collaborative Fund
"The correct lesson to learn from surprises is that the world is surprising." —Morgan Housel. "The Psychology of Prediction." Collaborative Fund. July 21, 2019.
Forecasting with R Script: Graph of WHO Flu Data
# flu.R # Original: November 2, 2018 # Last revised: December 3, 2018 ################################################# # Prep: Go to the WHO Flumart website: # http://apps.who.int/flumart/Default?ReportNo=12 # Select Year 2000 Week 1 to current year, week 52. # Save file to the data directory. Change weeks below. ################################################# # Description: # Script parses cvs file and provides … Continue reading Forecasting with R Script: Graph of WHO Flu Data
One and One Sometimes Equals Eleven
We often make assumptions that are reasonable in one context, abstract it into a guideline and apply that guideline to a new situation. Often, it is difficult to assess whether these situations are close enough to apply what we know to what we don't. At base, this is the problem of induction. There is no … Continue reading One and One Sometimes Equals Eleven
If You Say Something Is “Likely,” How Likely Do People Think It Is?
Suggestions for improving forecasting and communication about it: Use probabilities instead of words to avoid misinterpretation Use structured approaches to set probabilities Seek feedback to improve your forecasting —Andrew Mauboussin and Michael J. Mauboussin. "If You Say Something Is “Likely,” How Likely Do People Think It Is?" Harvard Business Review. July 3, 2018. Sites like … Continue reading If You Say Something Is “Likely,” How Likely Do People Think It Is?
