Understanding Moments
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Understanding Moments
A key aspect of thinking quantitatively is understanding the laws of probability and randomness.
Thomas H. Davenport • Keeping Up with the Quants: Your Guide to Understanding and Using Analytics
But it’s more important to understand the principles of calculus—where you’re measuring the change in small discrete or small continuous events.
Tim Ferriss • The Almanack of Naval Ravikant: A Guide to Wealth and Happiness
we also need a measure of the spread of the data around the average. The most common way to do this is using a metric called the standard deviation.
Jeff Sauro • Quantifying the User Experience: Practical Statistics for User Research
数据科学中的概率分布：从基础到复杂的全面指南🧠🦍
这张图展示了多种概率分布及其在数据科学中的应用。以下是一些常见的概率分布及其简单解释：
1. 正态分布（Normal Distribution）：钟形曲线，常用于自然现象的数据建模。
2. 二项分布（Binomial Distribution）：用于表示成功和失败两种结果的事件。
3. 泊松分布（Poisson Distribution）：用于描述单位时间内事件发生的次数。
4. 指数分布（Exponential Distribution）：用于表示时间间隔的概率，如客户到达时间。
5. 卡方分布（Chi-square Distribution）：用于假设检验和方差分析。
每种分布都有其特定的应用场景和参数，用于解决不同类型的问题。... See more
In our thinking square, a person’s x-axis position shows us where they landed at Point B—the output of their thinking process. Their y-axis position tells us about the kind of arrow that led them there—about the process and the rationale underlying what they believe.
Tim Urban • Page Not Found — Wait But Why
goals. The word understanding has various meanings, and our usage suggeststhat understanding is not one achievement but several, and it is revealedthrough different kinds of evidence.
Jay McTighe • Understanding by Design
How do you make sense of an “average” of a system that will be different every time you run it? Well, you could fix the period of time the system runs for and take the limit of where individual variables get to, as attained by running the system over and over and over to infinity. Or, you could fix the number of systems (preferably at “one” for min
... See moreSacha Meyers • Bitcoin Is Venice: Essays on the Past and Future of Capitalism
Because you can rarely measure an entire population, you usually don’t know the real value of a parameter. In fact, parameter values are almost always unknowable.