本课程《应用统计与数据分析:用 Python 和 ChatGPT 驱动洞察与决策》面向零基础学员,系统讲解统计分析的核心概念与实操技巧,帮助你掌握如何通过Python工具(如pandas、numpy、seaborn等)清洗、转换并分析真实数据,进而进行假设检验、回归建模和可视化表达。
你将学习如何使用均值、标准差、T检验、ANOVA、卡方检验等统计方法解读数据背后的意义,并借助 ChatGPT 提升分析效率与代码调试能力。适合希望进入数据分析领域、强化商业洞察力或提升统计技能的学生、职场人士与数据爱好者。通过实战操作,你将掌握将数据转化为战略决策的能力。
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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.
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