seasonal adjustment; seasonally adjusted (SA)

简明释义

季节性调整

英英释义

例句

1.When comparing monthly data, it is crucial to look at the seasonally adjusted (SA) (季节性调整) figures to get an accurate picture.

在比较每月数据时，查看季节性调整（SA）（季节性调整）数字以获得准确的情况至关重要。

2.Retail sales showed a significant increase, but the seasonally adjusted (SA) (季节性调整) numbers indicate a more stable growth.

零售销售显示出显著增长，但季节性调整（SA）（季节性调整）的数字表明更稳定的增长。

3.Analysts prefer using seasonally adjusted (SA) (季节性调整) data to eliminate fluctuations caused by seasonal patterns.

分析师更喜欢使用季节性调整（SA）（季节性调整）数据，以消除由季节模式引起的波动。

4.The unemployment rate was reported at 5%, but after applying seasonal adjustment (季节性调整), the true figure is closer to 4.8%.

失业率报告为5%，但经过季节性调整（季节性调整）后，真实数字接近4.8%。

5.The GDP growth rate was revised after seasonal adjustment (季节性调整), revealing a stronger economy than initially thought.

在进行季节性调整（季节性调整）后，GDP增长率被修订，显示出比最初认为的更强劲的经济。

作文

In the field of economics, data analysis plays a crucial role in understanding trends and making informed decisions. One important concept that analysts often encounter is seasonal adjustment; seasonally adjusted (SA). This term refers to the process of removing the effects of seasonal variations from data to reveal underlying trends more clearly. For instance, many economic indicators, such as employment figures, retail sales, and production outputs, can fluctuate significantly throughout the year due to seasonal factors like holidays, weather changes, or agricultural cycles. Without seasonal adjustment; seasonally adjusted (SA), these fluctuations can obscure the true performance of the economy, leading to potentially misleading conclusions.To illustrate this point, consider the retail sales data collected during the holiday season. Sales typically spike in December due to Christmas shopping, which can create an illusion of growth when viewed without context. By applying seasonal adjustment; seasonally adjusted (SA), analysts can strip away these seasonal effects and provide a clearer picture of the month-to-month changes in consumer spending. This allows policymakers and business leaders to make more accurate forecasts and strategic decisions.The methodology behind seasonal adjustment; seasonally adjusted (SA) involves statistical techniques that analyze historical data to identify and quantify seasonal patterns. Common methods include the X-12-ARIMA and X-13ARIMA-SEATS models, which are widely used by national statistical agencies. These models take into account various factors such as trends, cycles, and irregular components, enabling a more precise adjustment of the data.Moreover, it is essential to understand that while seasonal adjustment; seasonally adjusted (SA) provides valuable insights, it is not without limitations. The effectiveness of the adjustment depends on the quality and consistency of the underlying data. If there are significant changes in consumer behavior or external shocks, the historical patterns may not accurately predict future trends. Therefore, analysts must continuously evaluate and refine their seasonal adjustment processes to ensure they remain relevant and reliable.In conclusion, seasonal adjustment; seasonally adjusted (SA) is a vital tool in economic analysis that helps to clarify trends by eliminating seasonal effects. It allows for a more accurate interpretation of data, leading to better decision-making for businesses, governments, and researchers. As we navigate through an increasingly complex economic landscape, the importance of understanding and applying seasonal adjustment; seasonally adjusted (SA) cannot be overstated. By doing so, we can gain deeper insights into economic performance and enhance our ability to respond to changing conditions effectively.

在经济学领域，数据分析在理解趋势和做出明智决策中发挥着至关重要的作用。分析师经常遇到的一个重要概念是季节调整；季节性调整（SA）。这个术语指的是从数据中去除季节性变化的影响，以更清晰地揭示潜在趋势。例如，许多经济指标，如就业数字、零售销售和生产输出，可能因节假日、天气变化或农业周期等季节性因素而在一年中大幅波动。如果没有季节调整；季节性调整（SA），这些波动可能会掩盖经济的真实表现，导致潜在的误导性结论。为了说明这一点，考虑在假期季节收集的零售销售数据。由于圣诞购物，销售通常在十二月激增，这可能在没有背景的情况下造成增长的错觉。通过应用季节调整；季节性调整（SA），分析师可以消除这些季节性影响，从而提供消费者支出月度变化的更清晰图景。这使得政策制定者和商业领袖能够做出更准确的预测和战略决策。季节调整；季节性调整（SA）背后的方法涉及统计技术，这些技术分析历史数据以识别和量化季节性模式。常用的方法包括X-12-ARIMA和X-13ARIMA-SEATS模型，这些模型被国家统计机构广泛使用。这些模型考虑了趋势、周期和不规则成分等各种因素，从而能够更精确地调整数据。此外，了解虽然季节调整；季节性调整（SA）提供了宝贵的洞察，但并非没有局限性也至关重要。调整的有效性取决于基础数据的质量和一致性。如果消费者行为发生重大变化或外部冲击，历史模式可能无法准确预测未来趋势。因此，分析师必须不断评估和完善他们的季节调整过程，以确保其保持相关性和可靠性。总之，季节调整；季节性调整（SA）是经济分析中的一个重要工具，通过消除季节性影响来帮助澄清趋势。它允许对数据进行更准确的解释，从而为企业、政府和研究人员提供更好的决策依据。在我们应对日益复杂的经济环境时，理解和应用季节调整；季节性调整（SA）的重要性不容小觑。通过这样做，我们可以更深入地了解经济表现，并增强我们有效应对变化条件的能力。