Sept 30: Statistics in Practice

In our Briefing this week, we take a look at the role of statistics and analytics in war, from WWII to the present. Our curriculum spotlight is on our Rasch and IRT Mastery - key skills for those involved in designing, developing, and analyzing tests…

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Historical Spotlight: John Tukey

The statistician John Tukey is regarded by some as the father, or at least one of the fathers, of data science.  Before Tukey, statistics meant inference (p-values, ANOVA, etc.) and models. Tukey brought to the discipline a whole new perspective: exploring the data to see…

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Statistics at War

World War 2 gave the statistics profession its big growth spurt. Statistical methods such as correlation, regression, ANOVA, and significance testing were all worked out previously, but it was the war which brought large numbers of people to the field as a profession. They didn’t…

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Sept 24: Statistics in Practice

This week we take a look at the interesting statistical problem of false positives, which naturally arise when you do lots of diagnostic tests or hypothesis tests.  Our course spotlight deals with another aspect of multiple statistical studies - how to combine them into a…

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False Positive Rate – It’s Not What You Might Think

“A little knowledge is a dangerous thing,” said Alexander Pope in 1711; he could have been speaking of the use of statistics by experts in all fields. In this article, we look at three consequential mistakes in the field of statistics. Two of them are famous, the third required a deep dive into the corporate annual reports of

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Famous Errors in Statistics

“A little knowledge is a dangerous thing,” said Alexander Pope in 1711; he could have been speaking of the use of statistics by experts in all fields. In this article, we look at three consequential mistakes in the field of statistics. Two of them are famous, the third required a deep dive into the corporate annual reports of

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Puzzle: Surgery or Radiation

Several decades ago, the dominant therapies for lung cancer were radiation, which offered better short-term survival rates, and surgery, which offered better long-term rates. A thought experiment was conducted in which surgeons were randomly assigned to one of two groups and asked whether they would choose surgery. Group 1 was told: The one-month survival rate is 90%. Group 2 was told: There is 10% mortality in the first month. Yes, the two statements say the same thing. What did the two physician groups choose?

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Sept 10: Statistics in Practice

This week we look at the second most popular percentage in statistics: 80%. Our course spotlight is on: Oct 30 –Nov 27: Sample Size and Power Determination See you in class! Peter Bruce Founder, Author, and Senior Scientist The Popular 80% Researchers and analysts are…

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Type III Error

Type I error in statistical analysis is incorrectly rejecting the null hypothesis - being fooled by random chance into thinking something interesting is happening.  The arcane machinery of statistical inference - significance testing and confidence intervals - was erected to avoid Type I error.  Type II error…

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The Popular 80%

Researchers and analysts are familiar with the famous 5% benchmark in statistics, the typical probability threshold at which a result becomes statistically significant.  (The probability in question is the probability that a result as interesting as the real-life result will happen in the null model.) …

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Sept 2: Statistics in Practice

This week, our topic is Data Engineering, and we feature a guest blog by Will Goodrum, a data scientist at Elder Research. Our course spotlight is Oct 2 -30: Categorical Data Analysis See you in class! Peter Bruce Founder, Author, and Senior Scientist Four Common…

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Four Common Pitfalls in Data Engineering

By Will Goodrum* Your company has made it a strategic priority to become more data-driven. Good! A major anticipated component of this transition is to implement new data technology (e.g., a data lake). Resources are thrown at identifying source systems and pulling information into a…

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Relative Risk Ratio and Odds Ratio

The Relative Risk Ratio and Odds Ratio are both used to measure the medical effect of a treatment or variable to which people are exposed. The effect could be beneficial (from a therapy) or harmful (from a hazard).  Risk is the number of those having…

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