|
所在平台: Udemy |
课程主页: https://www.udemy.com/course/statistics-with-python/
课程评论：没有评论
Coursera 上的《使用 Python 进行数据分析的统计学》课程旨在帮助学员掌握统计学基础知识和数据分析技能，并通过 Python 实践应用。 **课程亮点：** * **无需编程基础：** 课程从 Python 基础讲起，适合零基础学员。 * **理论与实践结合：** 不仅讲解统计学概念和 Python 实现，还通过“1960年代”的计算器方法，帮助学员深入理解统计检验背后的直觉。 * **实用性强：** 学到的知识可直接应用于工作场所。 * **全面覆盖统计学领域：** * **描述性统计：** 均值、众数、中位数、四分位数、极差、四分位距、标准差等。 * **数据可视化：** 使用 Matplotlib.pyplot 和 Seaborn 库绘制直方图、箱线图、散点图等常用图表。 * **概率：** 基本概念、排列、组合。 * **总体与抽样：** 基本概念。 * **概率分布：** 正态分布、二项分布、泊松分布。 * **假设检验：** 单样本检验和双样本检验（z 检验、t 检验、F 检验、卡方检验）。 * **方差分析 (ANOVA)：** 手动计算和 Python 实现。 * **拟合优度检验** 和 **列联表**。 课程通过丰富的实例和数据集，帮助学员扎实掌握统计学理论，并能熟练运用 Python 进行数据分析。
Perform simple or complex statistical calculations using Python! - You don't need to be a programmer for this:)You are not expected to have any prior knowledge of Python. I will start with the basics. Coding exercises are provided to test your learnings.The course not only explains, how to conduct statistical tests using Python but also explains in detail, how to perform these using a calculator (as if, it was the 1960s). This will help you in gaining the real intuition behind these tests.Learn statistics, and apply these concepts in your workplace using Python.The course will teach you the basic concepts related to Statistics and Data Analysis, and help you in applying these concepts. Various examples and data-sets are used to explain the application.I will explain the basic theory first, and then I will show you how to use Python to perform these calculations.The following areas of statistics are covered:Descriptive Statistics - Mean, Mode, Median, Quartile, Range, Inter Quartile Range, Standard Deviation. Data Visualization - Commonly used plots such as Histogram, Box and Whisker Plot and Scatter Plot, using the Matplotlib.pyplot and Seaborn libraries.Probability - Basic Concepts, Permutations, Combinations Population and Sampling - Basic conceptsProbability Distributions - Normal, Binomial and Poisson Distributions Hypothesis Testing - One Sample and Two Samples - z Test, t-Test, F Test and Chi-Square TestANOVA - Perform Analysis of Variance (ANOVA) step by step doing the manual calculation and by using Python.The Goodness of Fit and the Contingency Tables.
