Multiple Regression Analysis of Factors Influencing Grain Yield

Since ancient times, China has been a major agricultural country and is now the world's top food producer. With second largest population in world, it of great relevance to investigate factors influencing grain production. In this paper, we look at main that affect yield. A simple multiple linear regression analysis was used develop model with fertiliser application, sown area, flooded farm machinery power labour as independent variables total annual production dependent variable. The resulting fitted well observations were each other. However, there serious covariance between variables, so tested concluded satisfied chi-squaredness, but more which affected building could cause distortion. So finally build stepwise ridge models respectively eliminate multicollinearity among order optimise model.