本課程《應用統計與數據分析：用 Python 和 ChatGPT 驅動洞察與決策》面向零基礎學員，系統講解統計分析的核心概念與實操技巧，幫助你掌握如何通過Python工具（如pandas、numpy、seaborn等）清洗、轉換並分析真實數據，進而進行假設檢驗、回歸建模和可視化表達。
你將學習如何使用均值、標準差、T檢驗、ANOVA、卡方檢驗等統計方法解讀數據背後的意義，並藉助 ChatGPT 提升分析效率與代碼調試能力。適合希望進入數據分析領域、強化商業洞察力或提升統計技能的學生、職場人士與數據愛好者。通過實戰操作，你將掌握將數據轉化為戰略決策的能力。
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教程名稱：Applied Statistics And Analytics In Python And Chatgpt
下載連結：https://www.nidown.com/chatgpt-322947.html
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最便捷、最實惠的 ChatGPT Plus 升級服務來了！！！
查看詳情：https://www.kkmac.com/go/chatgpt
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英文原版介紹
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.
