【中文版】

同比和环比是什么意思？

同比和环比是用来比较不同时期数据的统计指标，通常用于分析数据的趋势和变化。同比是指比较两个相同月份的数据，而环比则是指比较两个相邻月份的数据。

同比是指将本期数据与去年同期数据进行比较，以观察数据的同比增长情况。比如，2022年7月的销售额为100万元，而2021年7月的销售额为80万元，那么2022年7月的销售额同比增加了(100-80)/80×100%=25%。同比可以消除季节性因素和周期性因素对数据的影响，更能反映数据的长期趋势和变化。

环比是指将本期数据与上期数据进行比较，以观察数据的环比变化情况。比如，2022年6月的销售额为90万元，而2022年5月的销售额为100万元，那么2022年6月的销售额环比减少了(100-90)/100×100%=10%。环比可以反映数据的短期变化和波动，但容易受到季节性因素和周期性因素的影响。

同比和环比是常用的数据分析方法，可以用来比较不同时期的数据，以观察数据的增长或减少趋势。在分析数据时，同时使用同比和环比可以更全面地了解数据的走势和变化。

【英文版】

What do year-on-year and sequential growth mean?

Year-on-year and sequential growth are statistical indicators used to compare data from different periods, usually used to analyze data trends and changes. Year-on-year refers to comparing data from the same month in different years, while sequential growth refers to comparing data from相邻months in the same year.

Year-on-year growth compares the current period's data with that of the same period last year to observe the year-on-year growth rate of the data. For example, if the sales in July 2022 were 1 million yuan and the sales in July 2021 were 800,000 yuan, then the year-on-year growth rate of sales in July 2022 would be (1 million - 800,000) / 800,000 x 100% = 25%. Year-on-year growth can eliminate the impact of seasonal and cyclical factors on the data, and reflect the long-term trend and changes of the data more accurately.

Sequential growth compares the current period's data with that of the previous period to observe the sequential change in the data. For example, if the sales in June 2022 were 900,000 yuan and the sales in May 2022 were 1 million yuan, then the sequential growth rate of sales in June 2022 would be (1 million - 900,000) / 1 million x 100% = 10%. Sequential growth can reflect short-term changes and fluctuations in the data, but it is easily affected by seasonal and cyclical factors.

Year-on-year and sequential growth are commonly used data analysis methods that can be used to compare data from different periods to observe the trend of growth or decrease in the data. When analyzing data, using both year-on-year and sequential growth together can provide a more comprehensive understanding of the trend and changes in the data.