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Multiple regression analysis using climate variables

Jamainal, Nur Azilla and Yusof, Fadhilah (2015) Multiple regression analysis using climate variables. In: PSM 2014/2015 Proceeding-Industrial Mathematics (SSCM and Mathematics(SSCE), 2014/2015, Johor Bahru, Johor.

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Abstract

Regression analysis is very useful when it comes to study the relationship between variables. Regression analysis can identify the cause and effect of one variable to another variable. Variables is the main part in regression analysis. There are dependent variable (or criterion variable) and independent variable (or predictor variable). In multiple regression, the independent variables can be added more in the model then explain the cause and effect of dependent variable in more variations. Hence, dependent variable can be predicted by building better models using multiple regression analysis. The objective of this study comprises of (i) to determine correlation between temperature, humidity, wind, solar radiation and evaporation; and (ii) to build relationships between predictand with predictors using multiple linear regression.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:correlation between temperature, solar radiation and evaporation
Subjects:Q Science > QC Physics
Divisions:Science
ID Code:61443
Deposited By: Widya Wahid
Deposited On:25 Apr 2017 12:01
Last Modified:22 Aug 2017 15:14

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