mean range

简明释义

平均射程

英英释义

The mean range is a statistical measure that represents the average of the differences between the highest and lowest values in a dataset.

均值范围是一个统计量,表示数据集中最高值和最低值之间差异的平均值。

例句

1.The teacher explained that the mean range 平均范围 of the test scores was significantly lower than last year.

老师解释说,测试分数的mean range 平均范围明显低于去年。

2.To better understand the dataset, we calculated the mean range 平均范围 of the temperatures recorded over the month.

为了更好地理解数据集,我们计算了一个月内记录的温度的mean range 平均范围

3.By analyzing the mean range 平均范围 of the sales data, the manager identified seasonal trends.

通过分析销售数据的mean range 平均范围,经理识别出了季节性趋势。

4.In statistics, the mean range 平均范围 is often used to summarize data sets.

在统计学中,mean range 平均范围常用于总结数据集。

5.The mean range 平均范围 of customer satisfaction scores indicated areas for improvement.

客户满意度评分的mean range 平均范围显示了需要改进的领域。

作文

In the field of statistics, understanding the concept of mean range is essential for data analysis. The mean range refers to a statistical measure that combines the average (mean) of a dataset with the range, which is the difference between the highest and lowest values in that dataset. This dual focus allows researchers and analysts to gain insights into the variability and central tendency of the data they are studying. For instance, consider a classroom of students who have taken a math test. If the scores range from 60 to 100, the range would be 40 (100 - 60). To find the mean range, one would first calculate the mean score of the class. Suppose the mean score is 80. In this case, the mean range would provide a clearer picture of how the scores are distributed around that mean. This information can be particularly useful for educators who want to understand how well their students are performing overall and identify any outliers or areas needing improvement.The significance of the mean range extends beyond educational settings. In business, for example, companies often analyze sales data to determine performance metrics. By examining the mean range of sales figures over a specific period, businesses can identify trends, spot anomalies, and make informed decisions about inventory management and marketing strategies. A wider mean range may indicate inconsistencies in sales performance, prompting further investigation into the causes behind such fluctuations.Moreover, the mean range can also be applied in various scientific fields. Researchers studying environmental data, such as temperature variations over a year, may calculate the mean range to assess climate patterns. By analyzing the average temperature alongside the range of temperatures recorded, scientists can better understand climatic changes and their potential impacts on ecosystems.In conclusion, the mean range is a valuable statistical tool that aids in the interpretation of data across diverse fields. By providing insights into both the average and the variability of a dataset, it enhances our understanding of complex information. Whether in education, business, or scientific research, grasping the concept of the mean range enables individuals and organizations to make more informed decisions based on the data at hand. As we continue to navigate an increasingly data-driven world, mastering such concepts will undoubtedly prove beneficial in both personal and professional contexts.

在统计学领域,理解mean range的概念对于数据分析至关重要。mean range是指一种统计测量,它将数据集的平均值(mean)与范围结合在一起,而范围是指该数据集中最高值和最低值之间的差异。这种双重关注使研究人员和分析师能够深入了解他们所研究数据的变异性和集中趋势。例如,考虑一个参加数学考试的学生班级。如果分数范围从60到100,则范围为40(100 - 60)。要找到mean range,首先需要计算班级的平均分数。假设平均分数为80。在这种情况下,mean range将提供有关分数如何围绕该平均值分布的更清晰的图景。这些信息对于希望了解学生整体表现并识别任何异常或需要改进的领域的教育工作者尤为重要。mean range的重要性超越了教育环境。在商业中,例如,公司经常分析销售数据以确定绩效指标。通过检查特定时期内销售数字的mean range,企业可以识别趋势、发现异常,并就库存管理和营销策略做出明智的决策。较宽的mean range可能表明销售业绩不一致,促使进一步调查导致这种波动的原因。此外,mean range也可以应用于各个科学领域。研究环境数据的研究人员,例如,可能会计算mean range来评估一年的温度变化。通过分析平均温度以及记录的温度范围,科学家可以更好地理解气候变化及其对生态系统的潜在影响。总之,mean range是一种有价值的统计工具,有助于解读各个领域的数据。通过提供有关数据集的平均值和变异性的见解,它增强了我们对复杂信息的理解。无论是在教育、商业还是科学研究中,掌握mean range的概念使个人和组织能够根据手头的数据做出更明智的决策。随着我们继续在一个日益数据驱动的世界中航行,掌握这样的概念无疑将在个人和职业背景中证明其价值。