This study is to investigate the skill levels of the state government employees. The study proposed two predictor variables i.e. experiences and training perceptions associated with job performance. The questionnaire consisted of five pages close-ended was designed to measure (1) experience, (2) training perceptions and (3) job performance. Factors 1 to 2 are the independent variables and facto...

Methods We evaluated the leading hypotheses on biophysical factors affecting species richness for Breeding Bird Survey routes from areas with little influence of human activities. We then derived a best model based on information theory, and used this model to extrapolate SK across North America based on the biophysical predictor variables. The predictor variables included the latest and probab...

Regression problems with many potential candidate predictor variables occur in a wide variety of scientific fields and business applications. These problems require you to perform statistical model selection to find an optimal model, one that is as simple as possible while still providing good predictive performance. Traditional stepwise selection methods, such as forward and backward selection...

Many research studies have proved neural networks as a viable alternative to statistical models for classification tasks. However, compared with statistical models, neural networks have had the drawback of being unable to explain its classification logic until the development of rule extraction algorithms from trained neural networks. This research attempts to compare the results of the rule ex...

Proposed methods for prediction interval estimation focus on cases where input variables are numerical. Since categorical input variables can also be represented using numerical variables, such methods are applicable to most datasets. We propose a new prediction interval estimation method tailored for datasets with nominal input variables. This method has two main phases: I) modeling the output...