{"title":"用移动平均法分析预测销售的数据","authors":"S. Evdokimova, A. Zhuravlev","doi":"10.34220/mamsp_44-49","DOIUrl":null,"url":null,"abstract":"The paper discusses methods of data analysis for forecasting sales using the example of a BigCar retail store that sells spare parts for trucks. Based on the information on sales for the calen-dar year, using the moving average method in MS Excel, the forecast values were calculated for three periods. Analysis of the calculated data showed that the smallest relative deviation is given by a four-month period.","PeriodicalId":113054,"journal":{"name":"Materials of the All-Russian Scientific and Practical Conference \"Modern aspects of modeling systems and processes\"","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"ANALYSIS OF DATA FOR FORECASTING SALES BY THE MOVING AVERAGE METHOD\",\"authors\":\"S. Evdokimova, A. Zhuravlev\",\"doi\":\"10.34220/mamsp_44-49\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper discusses methods of data analysis for forecasting sales using the example of a BigCar retail store that sells spare parts for trucks. Based on the information on sales for the calen-dar year, using the moving average method in MS Excel, the forecast values were calculated for three periods. Analysis of the calculated data showed that the smallest relative deviation is given by a four-month period.\",\"PeriodicalId\":113054,\"journal\":{\"name\":\"Materials of the All-Russian Scientific and Practical Conference \\\"Modern aspects of modeling systems and processes\\\"\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Materials of the All-Russian Scientific and Practical Conference \\\"Modern aspects of modeling systems and processes\\\"\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.34220/mamsp_44-49\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Materials of the All-Russian Scientific and Practical Conference \"Modern aspects of modeling systems and processes\"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34220/mamsp_44-49","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ANALYSIS OF DATA FOR FORECASTING SALES BY THE MOVING AVERAGE METHOD
The paper discusses methods of data analysis for forecasting sales using the example of a BigCar retail store that sells spare parts for trucks. Based on the information on sales for the calen-dar year, using the moving average method in MS Excel, the forecast values were calculated for three periods. Analysis of the calculated data showed that the smallest relative deviation is given by a four-month period.
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