Python 与 ChatGPT 应用统计分析课：假设检验与回归建模实战入门

本课程结合 Python 与 ChatGPT，系统讲解描述性统计、假设检验与回归分析在数据洞察中的实际应用。你将学会使用 pandas、numpy、scipy、matplotlib 等工具清洗、处理真实数据，构建一套完整的数据分析流程。课程涵盖均值、中位数、方差、ANOVA、多种可视化图表，并通过实战代码深入解析统计建模逻辑。适合零基础学员入门数据分析，帮助你用 AI 与 Python 把数据转化为决策力。

本教程为高质量英文原版视频课程，英文基础较弱的同学可通过翻译插件辅助学习。

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教程名称：Applied Statistics And Analytics In Python And Chatgpt

下载连结：https://www.nidown.com/chatgpt-322947.html

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英文原版介绍

Published 1/2024
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.49 GB | Duration: 3h 33m

Use Statistics and Hypothesis Testing to Find Insights. Develop Regression Models and Turn Data into Strategic Actions.

What you’ll learn

Learn how to understand data and hone your skills in inferential, descriptive, and hypothesis testing statistics.
Discover how to use descriptive statistical measures, such as mean, median, variance, and standard deviation, to summarize and understand data.
Python tools for cleaning, modifying, and analyzing real-world data include pandas, numpy, seaborn, matplotlib, scipy, and scikit-learn.
Establish a methodical procedure for data analysis that includes conversion, cleaning, and the use of statistical techniques to guarantee quality and accuracy.
Learn how to set up, run, and comprehend one-sample, independent sample, crosstabulation, association tests, and one-way ANOVA for hypothesis testing.
Gaining a rudimentary understanding of regression analysis will enable you to foresee and model variable relationships—a critical skill for making informed deci
Use python to show complex, interactive statistical visualizations including box plots, KDE plots, clustered bar charts, histograms, heatmaps, and bar plots.
Full explanation on each Python code that is used to solve statistical challenges. This will make the use of statistical analysis more clear.

Requirements

No prior experience is required.
Beginners are most welcome.
Basic computer literacy.
Interest in data analysis and statistics.