| dc.description.abstract | In Statistics Regression analysis is defined as one of the methods used to
determine cause-and-effect relationships between one variable and another.
Regression consisting of only one independent variable and one dependent
variable is called simple linear regression and if there is more than one
independent variable it is called multiple linear regression. In this study the
authors aim to analyze the effect of land area (X1), productivity (X2), rainfall (X3)
on the amount of corn production using the ordinary least squares (OLS)
regression analysis method using secondary data from 2013 – 2022 which
obtained from the BPS website. From the results of the study, the effect of the
independent variables was 99.90% where of the three variables, land area and
productivity were the factors that most influenced the amount of corn production
in Deli Serdang Regency. Based on the results of statistical analysis, it can be said
that the OLS model is very relevant in explaining maize production where this
model successfully passed the assumption test (normality, multicollinearity,
heteroscedasticity, autocorrelation), f test, and significant t test. | en_US |
