unanalysed

简明释义

英[ʌnəˈnælɪzd]美[ʌnəˈnælɪzd]

未分析的，未解析的

英英释义

单词用法

同义词

反义词

例句

1.The counter-transference, as defined by Gitelson, represents the activation of unanalysed and unintegrated aspects of the analyst.

反移情，如Gitelson所定义的，代表了分析师未活化的和未整合的部分。

2.Those books can go unmarked, those markets unanalysed, that coronary unperformed.

书可以不署名，市场分析可以不做，甚至冠心手术也可以不做。

3.The counter-transference, as defined by Gitelson, represents the activation of unanalysed and unintegrated aspects of the analyst.

反移情，如Gitelson所定义的，代表了分析师未活化的和未整合的部分。

4.The data collected from the survey remains unanalysed, making it difficult to draw any conclusions.

从调查收集的数据仍然是未经分析的，这使得很难得出任何结论。

5.An unanalysed sample can lead to incorrect assumptions in research.

一个未经分析的样本可能会导致研究中的错误假设。

6.The report highlighted several areas of unanalysed data that could provide insights.

报告强调了几个未经分析的数据领域，这些领域可能提供见解。

7.Before making decisions, we cannot rely on unanalysed information.

在做决定之前，我们不能依赖未经分析的信息。

8.Her thesis included a section on unanalysed variables that could affect the results.

她的论文中包括了一部分关于可能影响结果的未经分析变量。

作文

In the realm of scientific research, the importance of data analysis cannot be overstated. Researchers often gather vast amounts of information, yet if it remains unanalysed, its potential is lost. This situation can lead to a plethora of missed opportunities in various fields, including medicine, environmental science, and social studies. For instance, consider a medical study that collects data on patient outcomes after treatment. If this data is left unanalysed, healthcare professionals may not be able to discern which treatments are most effective or identify trends that could lead to better patient care.Moreover, in the field of environmental science, researchers often collect data on pollution levels, climate change impacts, and biodiversity. Without proper analysis, this information remains unanalysed, hindering our understanding of critical issues facing our planet. An unanalysed dataset may contain valuable insights that could inform policy decisions, guide conservation efforts, and ultimately help protect our environment for future generations.In social sciences, the implications of unanalysed data are equally significant. Surveys and studies conducted on public opinion can provide a wealth of information about societal trends and issues. However, if the results are left unanalysed, they fail to contribute to our knowledge of human behavior and social dynamics. Policymakers rely on well-analyzed data to make informed decisions that affect communities. Therefore, unanalysed data can lead to ineffective policies that do not address the needs of the population.The consequences of leaving data unanalysed extend beyond individual studies; they can create a ripple effect across entire fields of research. When researchers do not analyze their findings, it can result in a lack of progress and innovation. The scientific community thrives on collaboration and sharing results, but if data remains unanalysed, it creates barriers to communication and understanding among scientists.Furthermore, the digital age has exacerbated the issue of unanalysed data. With the explosion of big data, organizations are inundated with information from various sources. Often, this data is collected but not analyzed due to resource constraints or a lack of analytical skills. As a result, valuable insights remain locked away in unanalysed datasets, preventing organizations from making data-driven decisions that could enhance their operations or improve customer experiences.To combat the problem of unanalysed data, it is crucial to invest in data literacy and analytical skills across all sectors. Education and training programs can equip individuals with the necessary tools to analyze data effectively. Additionally, promoting a culture of data analysis within organizations can encourage employees to prioritize data-driven decision-making.In conclusion, the phenomenon of unanalysed data poses significant challenges across various fields. Whether in healthcare, environmental science, social studies, or business, failing to analyze data can lead to missed opportunities and ineffective solutions. By recognizing the importance of data analysis and investing in the necessary skills and resources, we can unlock the full potential of the information at our disposal and drive meaningful progress in our respective fields.

在科学研究领域，数据分析的重要性不容低估。研究人员通常收集大量信息，但如果这些数据保持未分析，其潜力将会丧失。这种情况可能导致各个领域错失无数机会，包括医学、环境科学和社会研究。例如，考虑一个医疗研究，它收集了治疗后患者结果的数据。如果这些数据被留作未分析，医疗专业人员可能无法辨别哪些治疗最有效，或者识别出可以改善患者护理的趋势。此外，在环境科学领域，研究人员经常收集有关污染水平、气候变化影响和生物多样性的数据。如果没有适当的分析，这些信息将保持未分析，阻碍我们对面临重大问题的理解。一个未分析的数据集可能包含有价值的见解，这些见解可以为政策决策提供信息，引导保护工作，并最终帮助保护我们的环境，为未来几代人服务。在社会科学中，未分析数据的影响同样显著。对公众舆论进行的调查和研究可以提供大量关于社会趋势和问题的信息。然而，如果结果保持未分析，它们无法为我们对人类行为和社会动态的知识做出贡献。政策制定者依赖经过良好分析的数据来做出影响社区的明智决策。因此，未分析的数据可能导致无效的政策，无法满足人口的需求。将数据保持未分析的后果超出了个别研究的范围；它们可能在整个研究领域产生涟漪效应。当研究人员不分析他们的发现时，可能会导致缺乏进展和创新。科学界依靠合作和分享结果，但如果数据保持未分析，则会在科学家之间造成沟通和理解的障碍。此外，数字时代加剧了未分析数据的问题。随着大数据的爆炸，组织面临来自各种来源的信息轰炸。通常，这些数据被收集但由于资源限制或缺乏分析技能而未被分析。因此，有价值的见解仍然锁定在未分析的数据集中，阻止组织做出能够增强其运营或改善客户体验的数据驱动决策。为了解决未分析数据的问题，至关重要的是在各个行业投资于数据素养和分析技能。教育和培训项目可以使个人具备有效分析数据所需的工具。此外，在组织内部促进数据分析文化可以鼓励员工优先考虑基于数据的决策。总之，未分析数据现象在各个领域都带来了重大挑战。无论是在医疗、环境科学、社会研究还是商业中，未能分析数据可能导致错失机会和无效解决方案。通过认识到数据分析的重要性并投资于必要的技能和资源，我们可以释放手头信息的全部潜力，并推动各自领域的有意义进展。