Imam Hanafi

Modeling Asia's Child Mortality Rate: A Thinking of Human Development in Asia

Abstract Multiple linear regression model was employed to model child under age of five mortality rate and related factors in Asia of year 2010. Data analysis was carried out to find factors which influence the child mortality in Asia. Correlation analysis was done to check on the relationship among all the variables, as well as to identify the problem of multicollinearity in the data. Having fitted multiple linear regression, it was found that mortality rate of children under age of five in Asia countries are significantly influenced by percentage of case detection for all forms of tuberculosis, number of reported deaths on measles, number of population using an improved drinking water source, and number of birth trauma reported. Among those variable, it was identified that number of population using an improved drinking water source is the most important factor.

On the Performance of Several Approaches to Obtain Standardized Logistic Regression Coefficients

In general regression analysis, standardized beta weights are often used to compare strength of prediction across variables. In order to consider obtaining an estimation of standardized logistic regression coefficients, the model must be rescaled to include such coefficients. One of the reasons to have the coefficient standardized is we will have more informative coefficients compared to unstandardized coefficients, especially for variables which have no natural metric. Several approaches of obtaining standardized coefficients in logistic regression are available in literatures. This article studies the performance of the existing approaches to obtain standardized logistic regression coefficient based on real data.

Exploring central limit theorem on world population density data

We do some exploration to Central Limit Theorem on a real dataset. We intend to conduct this study to a real data which has non-normal distribution. Under common sense, it is known that world population density data has right-skewed distribution. A resampling mechanism is done to the original data by varying sample size to study the properties of well-known Central Limit Theorem, such as normality of the sampling distribution and reduction of the standard deviation of sample data due to larger sample size.