biological statistics

简明释义

生物统计学;

英英释义

例句

1.The application of biological statistics 生物统计学 can improve wildlife conservation efforts.

生物统计学的应用可以改善野生动物保护工作。

2.Students in the biology program must take a course in biological statistics 生物统计学 to graduate.

生物学专业的学生必须选修一门生物统计学课程才能毕业。

3.The study of biological statistics 生物统计学 helps researchers understand population dynamics.

对生物统计学的研究帮助研究人员理解种群动态。

4.In drug development, biological statistics 生物统计学 is crucial for analyzing clinical trial data.

在药物开发中，生物统计学对于分析临床试验数据至关重要。

5.Researchers used biological statistics 生物统计学 to evaluate the effectiveness of a new vaccine.

研究人员使用生物统计学评估新疫苗的有效性。

作文

In recent years, the field of science has made significant strides in understanding complex biological systems. One of the essential tools that researchers employ to make sense of biological data is biological statistics. This discipline combines the principles of statistics with biological research, allowing scientists to draw meaningful conclusions from their experiments and observations. The importance of biological statistics cannot be overstated, as it plays a critical role in various areas such as medicine, ecology, and genetics.To begin with, biological statistics provides the framework necessary for analyzing data collected from biological experiments. For instance, when studying the effects of a new drug on a particular disease, researchers must collect data from clinical trials. Here, biological statistics helps in determining whether the observed effects are statistically significant or merely due to random chance. By applying statistical tests, scientists can assess the efficacy of the drug and make informed decisions about its potential use in treatment.Moreover, biological statistics is crucial in ecological studies where researchers monitor populations of species over time. By employing statistical models, ecologists can predict population trends, understand the impact of environmental changes, and develop conservation strategies. For example, if a certain species is declining in numbers, biological statistics can help identify the factors contributing to this decline, whether they are related to habitat loss, climate change, or other human activities.Furthermore, in the realm of genetics, biological statistics is indispensable for analyzing genetic data. With the advent of technologies like genome sequencing, researchers generate vast amounts of data that require sophisticated statistical methods for analysis. These methods enable scientists to identify genetic markers associated with diseases, understand hereditary patterns, and explore evolutionary relationships among species. Without biological statistics, the interpretation of such complex datasets would be nearly impossible.In addition to its applications, biological statistics also fosters interdisciplinary collaboration. Biologists often work alongside statisticians to ensure that their experimental designs are robust and that the data analysis is sound. This collaboration enhances the quality of research, leading to more reliable results and advancements in our understanding of biological phenomena.However, it is essential to recognize that biological statistics is not without its challenges. Researchers must be careful in selecting appropriate statistical methods and interpreting results accurately. Misuse of statistical techniques can lead to erroneous conclusions, which may have serious implications, especially in clinical settings. Therefore, ongoing education and training in biological statistics are vital for scientists at all levels.In conclusion, biological statistics serves as a cornerstone in the biological sciences, enabling researchers to analyze data effectively and derive meaningful insights. Its applications span across medicine, ecology, and genetics, making it an invaluable tool in addressing some of the most pressing challenges in biology today. As we continue to explore the intricacies of life, the role of biological statistics will undoubtedly grow, further bridging the gap between data and biological understanding.

近年来，科学领域在理解复杂生物系统方面取得了显著进展。研究人员使用的一个重要工具是生物统计学。这个学科将统计学原理与生物研究相结合，使科学家能够从实验和观察中得出有意义的结论。生物统计学的重要性不容小觑，因为它在医学、生态学和遗传学等多个领域发挥着关键作用。首先，生物统计学提供了分析生物实验中收集的数据所需的框架。例如，在研究新药对特定疾病的影响时，研究人员必须从临床试验中收集数据。在这里，生物统计学帮助确定观察到的效果是否具有统计学意义，还是仅仅由于随机机会。通过应用统计检验，科学家可以评估药物的疗效，并就其潜在的治疗使用做出明智的决定。此外，生物统计学在生态学研究中至关重要，研究人员监测物种的种群变化。通过采用统计模型，生态学家可以预测种群趋势，理解环境变化的影响，并制定保护策略。例如，如果某个物种数量正在下降，生物统计学可以帮助识别导致这一下降的因素，无论是栖息地丧失、气候变化还是其他人类活动。此外，在遗传学领域，生物统计学对于分析遗传数据不可或缺。随着基因组测序等技术的出现，研究人员生成大量数据，这些数据需要复杂的统计方法进行分析。这些方法使科学家能够识别与疾病相关的遗传标记，理解遗传模式，并探索物种之间的进化关系。如果没有生物统计学，对如此复杂的数据集的解释几乎是不可能的。除了应用，生物统计学还促进了跨学科的合作。生物学家通常与统计学家合作，以确保他们的实验设计稳健，数据分析可靠。这种合作提高了研究的质量，导致更可靠的结果和我们对生物现象理解的进步。然而，必须认识到，生物统计学并非没有挑战。研究人员必须小心选择适当的统计方法并准确解释结果。统计技术的误用可能导致错误的结论，这可能在临床环境中产生严重影响。因此，持续的教育和培训对各级科学家来说在生物统计学领域至关重要。总之，生物统计学作为生物科学的基石，使研究人员能够有效分析数据并得出有意义的见解。它的应用跨越医学、生态学和遗传学，使其成为应对当今生物学一些最紧迫挑战的宝贵工具。随着我们继续探索生命的复杂性，生物统计学的角色无疑会增长，进一步弥合数据与生物理解之间的差距。