average normal interval

简明释义

平均正向磁化时段;

英英释义

例句

1.The average normal interval 平均正常间隔 between meals is typically four to six hours.

餐与餐之间的平均正常间隔 average normal interval 通常是四到六小时。

2.The average normal interval 平均正常间隔 for a woman's menstrual cycle is generally 28 days.

女性月经周期的平均正常间隔 average normal interval 通常为28天。

3.In our study, we found that the average normal interval 平均正常间隔 for sleep cycles is about 90 minutes.

在我们的研究中，我们发现睡眠周期的平均正常间隔 average normal interval 大约为90分钟。

4.For exercise routines, the average normal interval 平均正常间隔 between workouts should be at least 48 hours.

对于锻炼计划，锻炼之间的平均正常间隔 average normal interval 应至少为48小时。

5.The doctor explained that the average normal interval 平均正常间隔 between check-ups is usually six months.

医生解释说，检查之间的平均正常间隔 average normal interval 通常是六个月。

作文

In the realm of statistics and data analysis, understanding various terms is crucial for interpreting results accurately. One such term that often arises is the average normal interval. This concept plays a significant role in various fields, including psychology, finance, and health sciences. To grasp its meaning fully, we must break it down into its components and explore its applications.The term 'average' refers to a central value that summarizes a set of numbers. It can be calculated using different methods, including the mean, median, or mode. In most cases, the mean is the most commonly used form of average, which is calculated by summing all values and dividing by the number of values. Understanding the average helps researchers and analysts identify trends and make predictions based on data.Next, we have 'normal,' which in statistical terms, often relates to the normal distribution. A normal distribution is a bell-shaped curve that represents how data points are spread out around the mean. In a normal distribution, most of the observations cluster around the central peak, and probabilities for values further away from the mean taper off equally in both directions. This concept is vital as it allows analysts to understand the likelihood of certain outcomes occurring within a given range.Lastly, the term 'interval' refers to a range of values. In statistics, intervals can be used to describe confidence intervals, which give an estimated range of values that is likely to include an unknown population parameter. When we combine these three components, we arrive at the average normal interval, which signifies the range of values that fall within one standard deviation of the mean in a normal distribution.To illustrate this concept, let’s consider a practical example. Suppose a teacher has recorded the test scores of her students. After calculating the average score, she finds that the mean score is 75 with a standard deviation of 10. The average normal interval for the scores would then be between 65 and 85 (75 ± 10). This means that approximately 68% of the students scored within this range, according to the empirical rule of normal distributions.Understanding the average normal interval is essential for making informed decisions based on data. For instance, in healthcare, practitioners can use this concept to analyze patient data. If a doctor knows that a particular biomarker should fall within a specific average normal interval, they can quickly identify patients who are outside the norm and may require further evaluation.In finance, investors often rely on the average normal interval to assess the performance of stocks. By analyzing historical price data, they can determine the average return and the expected fluctuations, allowing them to make informed investment decisions.In conclusion, the average normal interval is a fundamental statistical concept that combines average values, normal distributions, and intervals. It serves as a powerful tool for interpreting data across various fields. By understanding this term, individuals can enhance their analytical skills and make better-informed decisions based on statistical evidence. As we continue to navigate through a data-driven world, mastering such concepts becomes increasingly important for success in both academic and professional settings.

在统计学和数据分析领域，理解各种术语对于准确解读结果至关重要。一个经常出现的术语是平均正常区间。这个概念在心理学、金融和健康科学等多个领域中发挥着重要作用。为了充分理解它的含义，我们必须将其分解为各个组成部分，并探讨其应用。“平均”一词指的是总结一组数字的中心值。它可以通过不同的方法计算，包括均值、中位数或众数。在大多数情况下，均值是最常用的平均值形式，通过将所有值相加并除以值的数量来计算。理解平均值有助于研究人员和分析师识别趋势并根据数据做出预测。接下来是“正常”，在统计学中，这个词通常与正态分布有关。正态分布是一个钟形曲线，表示数据点围绕均值的分布情况。在正态分布中，大多数观察值集中在中央峰附近，而远离均值的值的概率在两个方向上逐渐减小。这个概念至关重要，因为它使分析师能够理解在给定范围内某些结果发生的可能性。最后，“区间”一词指的是一系列值。在统计学中，区间可以用来描述置信区间，给出一个估计值范围，该范围很可能包括一个未知的总体参数。当我们将这三个组件结合起来时，就得出了平均正常区间，它表示在正态分布中，落在均值一个标准差范围内的值。为了说明这个概念，让我们考虑一个实际例子。假设一位老师记录了她学生的考试成绩。在计算出平均分后，她发现均分为75，标准差为10。那么，成绩的平均正常区间将是65到85（75 ± 10）。这意味着，根据正态分布的经验法则，大约68%的学生的分数在这个范围内。理解平均正常区间对于基于数据做出明智决策至关重要。例如，在医疗保健中，医生可以利用这个概念来分析患者数据。如果医生知道某个生物标志物应该落在特定的平均正常区间内，他们可以快速识别出超出正常范围的患者，并可能需要进一步评估。在金融领域，投资者通常依赖平均正常区间来评估股票的表现。通过分析历史价格数据，他们可以确定平均回报和预期波动，从而做出明智的投资决策。总之，平均正常区间是一个基本的统计概念，它结合了平均值、正态分布和区间。它作为一个强大的工具，用于解读各个领域的数据。通过理解这个术语，个人可以增强他们的分析能力，并根据统计证据做出更明智的决策。随着我们继续在数据驱动的世界中导航，掌握这些概念变得越来越重要，以便在学术和职业环境中取得成功。