seasonal estimate

简明释义

季节估计值

英英释义

例句

1.The seasonal estimate for agricultural yields is crucial for planning the harvest.

农业产量的季节性估计对收成规划至关重要。

2.The company released its quarterly report, highlighting the seasonal estimate for holiday sales.

公司发布了季度报告，强调了假期销售的季节性估计。

3.Retailers rely on the seasonal estimate to manage their inventory effectively.

零售商依靠季节性估计来有效管理他们的库存。

4.The seasonal estimate for tourism in summer shows a significant increase in visitors.

夏季的季节性估计显示游客数量显著增加。

5.Analysts often adjust their forecasts based on the seasonal estimate of demand during peak seasons.

分析师通常根据高峰季节的季节性估计来调整他们的预测。

作文

In the realm of economics and statistics, understanding various terms is crucial for accurate data interpretation. One such term that often arises in economic reports is seasonal estimate. A seasonal estimate refers to a statistical adjustment made to data to account for predictable seasonal fluctuations that occur during specific periods of the year. For example, retail sales typically increase during the holiday season, and this spike can skew monthly sales figures if not adjusted for. Therefore, economists use seasonal estimates to provide a clearer picture of underlying trends by removing these seasonal effects.The importance of seasonal estimates extends beyond just retail sales; it impacts various sectors, including agriculture, tourism, and even employment statistics. In agriculture, crop yields can vary significantly from season to season. By applying seasonal estimates, analysts can better understand the long-term productivity trends rather than being misled by seasonal highs or lows. Similarly, in tourism, visitor numbers may peak during summer months and dip in winter. Understanding these patterns through seasonal estimates enables businesses to prepare adequately for fluctuations in demand.Moreover, the methodology behind creating seasonal estimates involves sophisticated statistical models. Techniques such as the X-12-ARIMA and X-13-ARIMA-SEATS are widely used to decompose time series data into seasonal, trend, and irregular components. This decomposition allows statisticians to isolate the seasonal effects and create more reliable forecasts. For instance, if a company is analyzing its quarterly sales data, applying seasonal estimates can help distinguish between genuine growth and seasonal spikes, leading to more informed decision-making.In addition to their practical applications, seasonal estimates also play a vital role in policy-making. Governments and organizations rely on accurate economic indicators to formulate policies. If seasonal variations are not accounted for, policymakers may misinterpret economic health, potentially leading to misguided decisions. For example, during a period of economic downturn, if officials do not consider seasonal estimates, they might erroneously conclude that the economy is recovering based on seasonal hiring patterns during the holiday season.Furthermore, the concept of seasonal estimates has gained even more significance in recent years due to the impact of global events, such as the COVID-19 pandemic. Many industries experienced unprecedented changes in their seasonal patterns, making traditional seasonal estimates less reliable. As a result, economists have had to adapt their models to incorporate new data and adjust their expectations accordingly.In conclusion, the term seasonal estimate encapsulates a critical aspect of data analysis that aids in understanding economic trends by accounting for seasonal variations. Whether in retail, agriculture, or tourism, seasonal estimates provide valuable insights that help businesses and policymakers make informed decisions. As we continue to navigate an ever-changing economic landscape, the ability to accurately interpret and apply seasonal estimates will remain essential for effective planning and analysis.

在经济学和统计学的领域，理解各种术语对于准确的数据解读至关重要。一个经常出现在经济报告中的术语是季节性估计。季节性估计是指对数据进行的统计调整，以考虑在特定时间段内发生的可预测的季节性波动。例如，零售销售在假日季节通常会增加，这种激增如果不加以调整，会扭曲每月的销售数据。因此，经济学家使用季节性估计来提供更清晰的基本趋势图景，通过消除这些季节性影响。季节性估计的重要性不仅仅局限于零售销售，它还影响农业、旅游甚至就业统计等多个部门。在农业中，作物产量可能因季节而异。通过应用季节性估计，分析师能够更好地理解长期生产趋势，而不是被季节性的高低所误导。同样，在旅游业中，游客数量可能在夏季达到峰值，而在冬季下降。通过季节性估计理解这些模式使企业能够充分准备应对需求的波动。此外，创建季节性估计的方法论涉及复杂的统计模型。X-12-ARIMA和X-13-ARIMA-SEATS等技术被广泛用于将时间序列数据分解为季节性、趋势和不规则成分。这种分解使统计学家能够孤立季节性影响并创建更可靠的预测。例如，如果一家公司分析其季度销售数据，应用季节性估计可以帮助区分真正的增长和季节性激增，从而做出更明智的决策。除了实际应用之外，季节性估计在政策制定中也发挥着重要作用。政府和组织依赖准确的经济指标来制定政策。如果不考虑季节性变化，政策制定者可能会误解经济健康状况，从而导致错误的决策。例如，在经济下行时期，如果官员们不考虑季节性估计，他们可能会错误地得出经济在假日季节的季节性招聘模式基础上正在复苏的结论。此外，由于全球事件（如COVID-19大流行）的影响，季节性估计的概念在近年来变得更加重要。许多行业经历了前所未有的季节性模式变化，使传统的季节性估计变得不那么可靠。因此，经济学家不得不调整他们的模型，以纳入新数据并相应地调整预期。总之，术语季节性估计概括了数据分析的一个关键方面，通过考虑季节性变化来帮助理解经济趋势。无论是在零售、农业还是旅游业，季节性估计提供的宝贵见解帮助企业和政策制定者做出明智的决策。随着我们继续应对不断变化的经济形势，准确解读和应用季节性估计的能力将仍然是有效规划和分析的关键。