2012Crop ResearchRequires access

Tobacco Yield Prediction Model Based on SPSS Statistical Software in Baihe County

Li S

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Abstract

Actual production was separated into the trend of flue-cured tobacco yield and meteorological yield,according to the meteorological data and flue-cured tobacco production in 1997-2011 in Baihe,SPSS statistical software were used to establish trends of yield and meteorological yield regression model,and the production regression model eventual was established.Then the production of calendar year was tested,and the maximum prediction accuracy was 100%,the smallest accuracy was 92%,the average accuracy was 97%.The prediction model had a high reliability and practicality,it could be an effective tool for quantitative prediction.

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What this paper is about

Actual production was separated into the trend of flue-cured tobacco yield and meteorological yield,according to the meteorological data and flue-cured tobacco production in 1997-2011 in Baihe,SPSS statistical software were used to establish trends of yield and meteorological yield regression model,and the production regression model eventual was established.Then the production of calendar year was tested,and the maximum prediction accuracy was 100%,the smallest accuracy was 92%,the average accuracy was 97%.The prediction model had a high reliability and practicality,it could be an effective tool for quantitative prediction.

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Available abstract

Actual production was separated into the trend of flue-cured tobacco yield and meteorological yield,according to the meteorological data and flue-cured tobacco production in 1997-2011 in Baihe,SPSS statistical software were used to establish trends of yield and meteorological yield regression model,and the production regression model eventual was established.Then the production of calendar year was tested,and the maximum prediction accuracy was 100%,the smallest accuracy was 92%,the average accuracy was 97%.The prediction model had a high reliability and practicality,it could be an effective tool for quantitative prediction.

Key concepts: Curing of tobacco, Yield (engineering), Regression analysis, Statistical software, Statistics, Reliability (semiconductor), Regression, Environmental science

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