Regression analysis is a form of predictive modelling technique which investigates the relationship between adependent(target) andindependent variable (s)(predictor). This technique is used for forecasting, time series modelling and finding thecausal effect relationshipbetween the variables. For example, r...
It is one of the most widely known modeling technique. Linear regression is usually among the first few topics which people pick while learning predictive modeling. In this technique, the dependent variable is continuous, independent variable(s) can be continuous or discrete, and nature of regressi...
Inconditional models(also calleddiscriminative models), the sample is partitioned into input and output data, as in the regression example above. The statistical model is obtained by placing some restrictions on the conditional probability distribution of the outputs given the inputs. This is in con...
(1)).Furthermore,redundancy analysis and stepwise regression analysis revealed that changes in soil properties induced by nutrient addition and climate conditions jointly regulated changes in vegetation biomass and diversity.Conclusions:The plant biomass and diversity of three steppe types in Inner Mongolia...
3.A stepwise regression model was used for finding the relationship between lake water quality and urban land use types,and rural residential,urban residential,commercial land and bottomland were determined as the main sources of non-point source pollution(NPS).以武汉市汉阳区为例,利用逐步回归模型分...
The stepwise regression analysis indicated that the quality predication by using both two types of the glutenin was more reliable than that of each ... GE Shu-jun,XIE Ling-qin,WANG Jing-hua,... - 《Journal of Agricultural University of Hebei》 被引量: 8发表: 2002年 ...
Based on that, you can hypothesize proof and build a prediction of outcomes that support the same. You can also create a detailed stepwise plan for data collection, analysis, and testing. 2. Keep Your Questions Simple The surveys are meant to reach people en-masse, including awide demographic...
Binary Logistic stepwise regression analysis showed that low echo, aspect ratio ≥1 and strong echoes of types IV, V and VI were independent predictors of malignant thyroid nodules (OR=4.289, 4.051, 3.333, 4.047, 4.112, P<0.05), while strong echoes of types I and II were independent ...
Variables that were statistically significant in the univariate analysis were included in the stepwise binary logistic regression analysis. In univariate analysis, all covariables (P < 0.05) except gender (P=0.077) were statistically significant. In the significance test of measurement data, age P <...
Stepwise regression method was indicated that, seed size was the first (x1) and shoot length was the second (x2) independent variable that could be used to describe the trend of variation in seedling growth rate as dependent variable (Y) (R2 = 0.85). It was observed that by increasing ...