Topic: Statistics


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An Accelerated Master’s Degree: Data Mining in a Book (or Two)

DataMining

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There have been plenty of books recently published on the concept of Deliberate Practice, which essentially says that it takes 10,000 hours of a certain kind of practice (called ‘deliberate’) to gain expertise in something.   It makes sense that the majority of what we want to learn in any discipline is going to be experiential (or gained through practice).  But in order to better understand our experiences, we want to have some kind of framework of what to expect.  We want to develop a theory structure.

Books are what give us this theory structure, and certainly the quality of the theory structure we begin with impacts the amount of deliberate practice we need to become an ‘expert.’  So it’s important to choose the right books, as they will provide the base infrastructure upon which we will layer our experiences.  We’re looking for books that concisely capture the overriding concepts of a particular discipline.

And in any discipline, at least one fairly well defined, there doesn’t need to be that many books to accomplish this.  I would generally say that 3 books or fewer, for each discipline, will give you a proper theory structure.

With that in mind, let’s look at Data Mining…  Read More »

How to Avoid Vanity Metrics: Getting Under the Hood of Business

VanityMetrics

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Mental Models Used: ,

Most organizations have analysts reviewing financial and operational information on a regular basis – the objective being to gain some kind of meaning from information, and to capture that meaning with a metric or metrics.  Analysts are generally providing descriptive information (telling us how we’ve done) or predictive information (telling us how we suspect we will do).

But many commonly used metrics don’t provide any actionable insight.  In other words, they’re just for show.  These are called vanity metrics.  Other times metrics don’t properly measure the underlying data, potentially resulting in what only appears to be a valid metric on the surface.  This is called an Isomorphism.

A metric is only as valuable as its ability to decipher underlying data.  When metrics are properly developed and implemented, they become meaningful because they capture the drivers that lead to the behaviors and decisions desired.

A great resource for understanding metrics is the book Lean Analytics.  Although geared to start-ups, the logic used is widely applicable to organizations large and small.  You will find much of this logic in the following paragraphs.  Read More »

Finding Angels in the Details: The Value of Information

InformationLayers

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Many of the most powerful inventions throughout human history, from language to the modern computer, were those that enabled people to better generate, capture, and consume data and information.  And at no time in our history have we captured more data than we do today.  McKinsey estimates that global data is growing at a rate of 40% per year.  The more data captured, the more opportunity for enhanced decision-making.  But in order for that to happen, data must be turned into information, and information must be turned into knowledge.  Read More »

Giving Information Meaning: The Rise of Business Analytics

BAnalytics

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Business Analytics is the scientific process of transforming data into insight for making better decisions.  Data doesn’t always cooperate with this process, as it is often massive and messy.  But no matter what condition data is in, we use business analytics to make decisions with it.

In order to make these decisions, we have to understand the ultimate value that various combinations of this data can present.  So, we measure it.  That is, we measure what data carries: information.  Measurement is what informs uncertain decisions, and almost all decisions are made under uncertainty.  Read More »

An Accelerated Master’s Degree: Statistics in a Book (or Two)

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Topics: Statistics
Statistics

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There have been plenty of books recently published on the concept of Deliberate Practice, which essentially says that it takes 10,000 hours of a certain kind of practice (called ‘deliberate’) to gain expertise in something.   It makes sense that the majority of what we want to learn in any discipline is going to be experiential (or gained through practice).  But in order to better understand our experiences, we want to have some kind of framework of what to expect.  We want to develop a theory structure.

Books are what give us this theory structure, and certainly the quality of the theory structure we begin with impacts the amount of deliberate practice we need to become an ‘expert.’  So it’s important to choose the right books, as they will provide the base infrastructure upon which we will layer our experiences.  We’re looking for books that concisely capture the overriding concepts of a particular discipline.

And in any discipline, at least one fairly well defined, there doesn’t need to be that many books to accomplish this.  I would generally say that 3 books or fewer, for each discipline, will give you a proper theory structure.

With that in mind, let’s look at Statistics…  Read More »

Mingle with Powerful Models: Using Mental Models to Make Better Decisions

French Clock

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Charlie Munger likes to say that 80-90 mental models will give you the bulk of the material you need to be a “worldly-wise” person.  Part of being worldly-wise is making good decisions, and although Charlie mentions 95 models in his book (by my count), they can each be used and combined for different purposes.

So, how do we combine them to create the ideal decision-making process?  Since I’m in love with the number 7 (figuratively), I’ve put together what I consider the seven most useful mental models in decision-making.  Good decision-making will involve an understanding of Statistics, Economics, and Psychology.  And the decision-making process becomes much easier if you take mental models from these disciplines and put them into a checklist.  To me, the following seven mental models are the best checklist available.  Read More »