Narrow Results

It is not always easy, not only for beginners but also for experts, to find out newly research subjects or grasp analytically research trends (or directions). This work is one of the intelligent tasks. Traditionally, some investigations or research projects focused on the challengeable task of human-oriented creativeness: The efforts are very stable and the results make the basic framework or fundamental ideas clear one by one for strictly-constrained application of human-activity. This task is closely dependent on the global framework of knowledge management with respect to the support from human creative activity. In this paper, we discuss a computer-support method to arrange already-read papers analytically and then discuss the research topics related to currently focused research fields or research trends derived from the existing papers and researcher's interests. Our idea is to realise this paper inquiry method in three procedural steps, such as arranging paper contents, grasping relationships among papers and investigating research subjects followed by already-referred papers, and also make users interact with individually-generated results by controlling spirally three steps.

The following sections are included:

• INTRODUCTION

• POPULATION PARAMETERS AND THE REGRESSION MODELS
  • Data Description
  • Building the Population Regression Model
  • Sample Versus Population Regression Model

• THE LEAST-SQUARES ESTIMATION OF α AND β
  • Scatter Diagram
  • The Method of Least Squares
  • Estimation of Intercept and Slope

• STANDARD ASSUMPTIONS FOR LINEAR REGRESSION

• THE STANDARD ERROR OF ESTIMATE AND THE COEFFICIENT OF DETERMINATION
  • Variance Decomposition
  • Standard Error of Residuals (Estimate)
  • The Coefficient of Determination

• THE BIVARIATE NORMAL DISTRIBUTION AND CORRELATION ANALYSIS
  • The Sample Correlation Coefficient
  • The Relationship Between r and b
  • The Relationship Between r and R²

• Summary

• Appendix 13A Derivation of Normal Equations and Optimal Portfolio Weights

• Appendix 13B The Derivation of Equation 13.16

• Appendix 13C The Bivariate Normal Density Function
  • Using a Mathematics Aptitude Test to Predict Grade in Statistics

• Appendix 13D American Call Option and the Bivariate Normal CDF
  • Valuating American Option

• Questions and Problems