mean deviation

简明释义

平均偏差

英英释义

例句

1.A lower mean deviation indicates that the data points are closer to the mean, suggesting less variability.

较低的均方差表明数据点更接近均值，暗示变异性较小。

2.The mean deviation provides insight into the consistency of the measurements taken during the study.

在研究过程中，均方差提供了对测量一致性的洞察。

3.To assess the reliability of the experiment, we calculated the mean deviation of the results.

为了评估实验的可靠性，我们计算了结果的均方差。

4.In finance, calculating the mean deviation can help investors understand the volatility of their portfolio.

在金融领域，计算均方差可以帮助投资者了解其投资组合的波动性。

5.The mean deviation is a useful measure of dispersion in statistics, as it shows how much the data varies from the average.

在统计学中，均方差是一个有用的离散度衡量标准，因为它显示了数据与平均值的偏差程度。

作文

In statistics, understanding the concept of mean deviation is crucial for analyzing data sets. The mean deviation (平均偏差) provides a measure of how much the values in a data set deviate from the average value, or mean. This statistical tool is particularly useful because it gives insight into the variability and dispersion of the data, which can be essential for making informed decisions based on that data.To calculate the mean deviation, one must first determine the mean of the data set. Once the mean is established, the absolute deviations of each data point from the mean are calculated. These absolute deviations are then averaged to produce the mean deviation. This process allows researchers and analysts to quantify how spread out the values are relative to the mean, offering a clearer picture of the data's distribution.For instance, consider a simple data set representing the ages of a group of people: 20, 22, 24, 26, and 30. First, we would calculate the mean: (20 + 22 + 24 + 26 + 30) / 5 = 24. Next, we find the absolute deviations from the mean: |20 - 24| = 4, |22 - 24| = 2, |24 - 24| = 0, |26 - 24| = 2, and |30 - 24| = 6. The average of these absolute deviations gives us the mean deviation: (4 + 2 + 0 + 2 + 6) / 5 = 2.8. Thus, the mean deviation for this data set is 2.8 years.The mean deviation is particularly advantageous compared to other measures of dispersion, such as variance and standard deviation, because it is less sensitive to extreme values. In many scenarios, especially in business and economics, data sets can include outliers that may skew results significantly. The mean deviation offers a more robust understanding of the data's central tendency without being overly influenced by these outliers.Moreover, the mean deviation can be applied in various fields, including finance, quality control, and social sciences. For example, in finance, investors often look at the mean deviation of stock prices to assess risk. A lower mean deviation indicates that the stock's price remains close to the average, suggesting stability, whereas a higher mean deviation implies greater volatility and risk.In summary, the mean deviation (平均偏差) is a fundamental statistical measure that helps us understand the variability of data sets. By providing a clear and concise way to assess how individual data points differ from the mean, it enables better decision-making across various domains. Whether in academic research, business analytics, or everyday problem-solving, mastering the concept of mean deviation is essential for anyone looking to work effectively with data.