1) 二项分布 二项分布(伯努利分布)是n个独立的是/非试验中成功的次数的概率分布,其中每次试验的成功概率为p。这是一个离散分布,所以使用概率质量函数(PMF)来表示k次成功的概率: 最常见的二项分布就是投硬币问题了,每次投一个硬币,投n次硬币,正面朝上次数就满足该分布。size(投掷次数)可以从10~10000. 看图形的
In this Chapter, we introduce few concepts of probability and statistics. We begin with simple statistical averages and the definition of probability. We then consider discrete probability distributions like the binomial and the Poisson functions. This is followed by the continuous probability ...
These tutorials dive into the concept of cumulative distribution functions (CDFs), which are used to quantify the probability that tells us the probability that a random variable takes on a value less than or equal to some threshold value. They are another crucial element in various statistical i...
This textbook, featuring Python 3.7, covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules. Features fully updated explanation on how to simulate, conceptualize, and visualize random statistical pro
Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python programming....
In this four-hour course, you’ll learn the basics of analyzing time series data in Python. Start Course for Free Included withPremium or Teams PythonProbability & Statistics4 hours17 videos59 Exercises4,850 XP63,981Statement of Accomplishment ...
1 Introduction to Statistics in Python Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python. Course 2 Introduction to Regression with statsmodels in Python Predict housing prices and ad click-through rate by implementing, analyzing, and...
In this step-by-step tutorial, you'll learn the fundamentals of descriptive statistics and how to calculate them in Python. You'll find out how to describe, summarize, and represent your data visually using NumPy, SciPy, pandas, Matplotlib, and the built
Blitzstein和Jessica Hwang写的Introduction to Probability。另外一本非常有用的书是Sumio Watanabe写的Mathematical Theory of Bayesian Statistics,该书比第一本更偏向贝叶斯统计,也更侧重数学。 1.2.1 解释概率 尽管概率论是一个相当成熟和完善的数学分支,但关于概率的诠释不止一种。从贝叶斯的角度看,概率是衡量某一...
to probability and statistics. Furthermore, we also assume that you have a good grasp of the basic mechanics of the Python language itself. Having said that, this book is appropriate if you have this basic background and want to learn how to use the ...