通过ChatGPT-4和o3-mini模型确认SPSS结果
Frederick Strale1, Isaac Riddle2, Bowen Geng2
1Biostatistics, The Oxford Center, Brighton, USA.
Cureus
|May 12, 2025
概括
在基本的统计分析中,ChatGPT-4与SPSS非常接近,但在复杂的程序中显示出差异. 聊天GPT-3.5-mini在相关性和多变量分析中表现出计算偏差,需要进一步改进科学研究的AI模型.
科学领域:
- 行为医疗数据分析数据分析
- 人工智能在统计学中的应用
- 计算社会科学 计算社会科学
背景情况:
- 统计软件 (SPSS) 与人工智能语言模型 (ChatGPT-4,ChatGPT-3.5-mini) 的数据分析比较.
- 评估AI在行为医疗研究中的定量性能,可解释性和伦理考虑.
- 评估AI的适应性和统计数据输出和解释的未来趋势.
研究的目的:
- 为了比较SPSS的统计输出和解释准确性与ChatGPT-4和ChatGPT-3.5-mini.
- 在行为医疗数据分析中评估人工智能模型的方法方法和定量性能.
- 确定AI驱动的科学研究统计分析的局限性和改进领域.
主要方法:
- 对两个真实世界的行为医疗数据集进行了14次统计分析.
- 使用描述性统计,皮尔森r,斯皮尔曼的rho,t测试,ANOVA和回归分析.
- 将口头命令和SPSS变量输入到ChatGPT-4和ChatGPT-3.5-mini中进行比较分析.
主要成果:
- 对于基本的统计分析 (例如,中心趋势,简单的相关性,t测试),SPSS和ChatGPT-4之间的高度一致性.
- 与SPSS相比,ChatGPT-4在简单线性回归中显示出最小的效果大小变化.
- 在复杂分析中观察到的差异;ChatGPT-3.5-mini在多变量程序中表现出膨胀的相关性和错误的结果.
结论:
- 聊天GPT-4在基本的统计测试中表现强,与SPSS.密切相似.
- 人工智能模型显示出潜力,但需要进一步验证和完善复杂的统计分析.
- 在先进的统计建模中,ChatGPT-3.5-mini的不一致性限制了它目前在科学研究应用中的可靠性.
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