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所在平台: Udemy |
课程主页: https://www.udemy.com/course/probability-and-statistics-complete-course/
课程评论：没有评论
课程名称：概率与统计：完整课程2025 概述：本课程旨在帮助学习者从初学者成长为概率与统计领域的专家。课程具有实践性，适合任何希望在数据科学、商业分析或其他领域利用统计学做出更明智决策的学习者。课程中包含丰富的视频示例和解释，确保每位学员不会迷失方向，所有技巧均在Microsoft Excel中实施，便于立即应用。 课程涵盖的主要内容包括： - 描述统计：均值、离散度量、相关性等。 - 数据清洗：识别和去除异常值。 - 数据可视化：所有标准的数据可视化技术，嵌入在Excel中。 - 概率：独立事件、条件概率和贝叶斯统计。 - 离散分布：二项分布、泊松分布、期望和方差及其近似。 - 连续分布：正态分布、中心极限定理和连续随机变量。 - 假设检验：利用二项、泊松和正态分布进行T检验和置信区间分析。 - 回归分析：线性回归分析、相关性检验和非线性回归模型。 - 测试质量：第一类和第二类错误、统计功效与样本量、p-hacking。 - 卡方检验：卡方分布以及如何使用它进行关联性和适合度检验。 还有更多精彩内容！本课程不要求先前的知识，除了最后连续分布章节中的2个可选视频需要有微积分基础。
This is course designed to take you from beginner to expert in probability and statistics. It is designed to be practical, hands on and suitable for anyone who wants to use statistics in data science, business analytics or any other field to make better informed decisions.Videos packed with worked examples and explanations so you never get lost, and every technique covered is implemented in Microsoft Excel so that you can put it to use immediately.Key concepts taught in the course are:Descriptive Statistics: Averages, measures of spread, correlation and much more.Cleaning Data: Identifying and removing outliersVisualization of Data: All standard techniques for visualizing data, embedded in Excel.Probability: Independent Events, conditional probability and Bayesian statistics.Discrete Distributions: Binomial, Poisson, expectation and variance and approximations.Continuous Distributions: The Normal distribution, the central limit theorem and continuous random variables.Hypothesis Tests: Using binomial, Poisson and normal distributions, T-tests and confidence intervals.Regression: Linear regression analysis, correlation, testing for correlation, non-linear regression models.Quality of Tests: Type I and Type II errors, power and size, p-hacking.Chi-Squared Tests: The chi-squared distribution and how to use it to test for association and goodness of fit.Much, much more!It requires no prior knowledge, with the exception of 2 optional videos at the end of the continuous distribution chapter, in which knowledge of calculus is required).
