The Improvement of Statistical Techniques in Biology
生物学中统计技术的改进AI 解读 ↓
← 返回论文列表与筛选
阅读说明
本页整理公开书目信息，不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成，未完成全文核验，可能有误；具体假设、证明与结论请核对原文。摘要保留来源文本，未经模型改写。
DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要；缺少可靠材料时保留待补状态。
引用量采用 OpenAlex 单条关联记录，不合计多个记录；关联记录可能包含正式发表版本，不等于此版本单独引用。缺失不视为零，引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配，同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列，再参考通用方法与发表日期。
分类依据与纠错
AI 根据所提供的论文材料归类：材料讨论一般实验设计与统计分析的协调，缺少所列因果识别或其他细分方法的具体依据。
反馈分类问题正在核对关联版本…
代码、数据与补充材料
正在核对对应版本的资源…
关注这篇论文的作者
生物学中统计技术的改进
- 研究问题
- 生物实验应如何在开展之前协调实验设计与统计方法，使目标效应的估计和误差评估获得适当的设计基础？
- 方法与思路
- 所给摘要以统计学家介入实验设计的历史变化展开论述，强调同时确定实验计划与分析方法，避免事后补救设计缺陷。
- 材料陈述的贡献
- 材料强调效应无偏估计与有效误差估计应由设计共同支持，并主张实验开始前整合设计和方法；未提出具体新估计量。
- 阅读关注点
- 应核对文中采用的实验设计原则、无偏性与误差估计的条件，以及所谓明确答案的适用范围和是否有具体实例支持。
- 阅读边界
- 依据版本未注明的 OpenAlex 索引摘要；不能推断刊本变化。材料的概括性主张不能替代具体假设，摘要也未提供定理或实验结果。
原文摘要
THE ENTRANCE of the statistician into the field of experimental design is the most outstanding feature of modern statistics. No more than a decade past, the statistician was distinctly on the defensive. When the data from an experiment were placed on his desk, he was supposed to produce some method of treatment irrespective of design. In some instances he was lucky; in others, baffled. Under the leadership of R. A. Fisher, the statistician has become the aggressor. He has found that the key to the problem is the intimate relation between the statistical method and the experimental plan. The latter must be capable of producing not only an unbiased estimate of the desired effects, but also a valid estimate of error. Many of the plans in use did neither. The statistician is now able to assert that properly designed experiments yield unqualified answers to the questions asked. It is incumbent upon the investigator to plan his experiment in accord with established principles, if he wishes to avail himself of adequate statistical methods. Only if the plan and the method are compatible may unambiguous conclusions be drawn from the statistics. To insure this, the statistical method must be decided upon along with the experimental plan before the laboratory or field work is initiated. The integration of plan and method lead to efficient designs.