mean deviation

简明释义

平均偏差

英英释义

例句

1.Researchers reported a low mean deviation 平均偏差 in their experimental results, indicating high precision.

研究人员报告他们的实验结果中mean deviation 平均偏差较低，表明高精度。

2.The statistician calculated the mean deviation 平均偏差 of the data set to understand its variability.

统计学家计算了数据集的mean deviation 平均偏差以理解其变异性。

3.By analyzing the mean deviation 平均偏差, we can identify outliers in our data.

通过分析mean deviation 平均偏差，我们可以识别数据中的异常值。

4.The mean deviation 平均偏差 is often used in finance to measure the risk associated with an investment.

在金融中，mean deviation 平均偏差常用于衡量与投资相关的风险。

5.In quality control, the mean deviation 平均偏差 helps to assess the consistency of manufacturing processes.

在质量控制中，mean deviation 平均偏差有助于评估制造过程的一致性。

作文

In the field of statistics, understanding the concept of mean deviation is crucial for analyzing data sets. The mean deviation refers to the average of the absolute differences between each data point and the overall mean of the dataset. This measure provides insight into the dispersion or variability of the data, allowing researchers to assess how spread out the values are around the mean. By calculating the mean deviation, one can obtain a clearer picture of the consistency or instability within the data, which is essential in various applications such as quality control, finance, and scientific research.To illustrate the significance of mean deviation, consider a simple example involving test scores from a classroom. Suppose five students scored 70, 75, 80, 85, and 90 on a math test. First, we calculate the mean score: (70 + 75 + 80 + 85 + 90) / 5 = 80. Next, we determine the absolute deviations from the mean:- For 70: |70 - 80| = 10- For 75: |75 - 80| = 5- For 80: |80 - 80| = 0- For 85: |85 - 80| = 5- For 90: |90 - 80| = 10Now, we find the mean deviation by averaging these absolute deviations: (10 + 5 + 0 + 5 + 10) / 5 = 6. This result indicates that, on average, the test scores deviate from the mean score of 80 by 6 points.Understanding the mean deviation is particularly valuable when comparing different datasets. For instance, if another group of students had scores of 60, 70, 80, 90, and 100, their mean deviation would be calculated similarly. The mean score for this group would be (60 + 70 + 80 + 90 + 100) / 5 = 80, and the absolute deviations would be:- For 60: |60 - 80| = 20- For 70: |70 - 80| = 10- For 80: |80 - 80| = 0- For 90: |90 - 80| = 10- For 100: |100 - 80| = 20The mean deviation for this second group would be (20 + 10 + 0 + 10 + 20) / 5 = 14. Although both groups have the same mean score, the second group has a higher mean deviation, indicating greater variability in their scores.In conclusion, the mean deviation is a vital statistical tool that helps in understanding the spread of data points in relation to the mean. It provides a straightforward way to quantify variability and can be applied across various fields, making it an essential concept for anyone working with data. Whether in academic research, business analytics, or everyday decision-making, grasping the implications of mean deviation can lead to more informed conclusions and strategies.

在统计学领域，理解均方差的概念对于分析数据集至关重要。均方差是指每个数据点与数据集整体均值之间绝对差异的平均值。这一度量提供了数据分散或变异性的洞察，使研究人员能够评估数值围绕均值的分布情况。通过计算均方差，人们可以更清晰地了解数据的一致性或不稳定性，这在质量控制、金融和科学研究等各个应用中都是必不可少的。为了说明均方差的重要性，考虑一个涉及课堂考试成绩的简单例子。假设五名学生在数学测试中分别得分70、75、80、85和90。首先，我们计算平均分： (70 + 75 + 80 + 85 + 90) / 5 = 80。接下来，我们确定与均值的绝对偏差：- 对于70: |70 - 80| = 10- 对于75: |75 - 80| = 5- 对于80: |80 - 80| = 0- 对于85: |85 - 80| = 5- 对于90: |90 - 80| = 10现在，我们通过平均这些绝对偏差来计算均方差：(10 + 5 + 0 + 5 + 10) / 5 = 6。这个结果表明，平均而言，测试成绩与80的均值偏离了6分。理解均方差在比较不同数据集时特别有价值。例如，如果另一组学生的分数为60、70、80、90和100，他们的均方差将以类似方式计算。该组的平均分为(60 + 70 + 80 + 90 + 100) / 5 = 80，绝对偏差为：- 对于60: |60 - 80| = 20- 对于70: |70 - 80| = 10- 对于80: |80 - 80| = 0- 对于90: |90 - 80| = 10- 对于100: |100 - 80| = 20这第二组的均方差为(20 + 10 + 0 + 10 + 20) / 5 = 14。尽管两个组的平均分相同，但第二组的均方差更高，表明其分数的变异性更大。总之，均方差是一个重要的统计工具，有助于理解数据点相对于均值的分布情况。它提供了一种简单的方法来量化变异性，可以广泛应用于各个领域，使其成为任何处理数据的人必须掌握的概念。无论是在学术研究、商业分析还是日常决策中，掌握均方差的含义都能带来更明智的结论和策略。