The Perception of Manobo Tribe on Different Aspects of Life: Their Effects on the Living and Social Conditions in San Luis, Agusan Del Sur

The study attempted to determine the perception of the Manobo tribe and their effect on their living and social conditions in Barangay Sta. Ines, San Luis Agusan del Sur. The descriptive method was used in this study describes the perception among the Manobo tribe on different aspects of life: their living and social conditions.  This study was conducted in barangay Sta. Ines, san Luis Agusan Del Sur.  There were only 195 of them who were taken as the respondents and researcher used the standardized questionnaire which were taken from the book of Mendez and used by the previous researchers. Hence, no validation was needed.  The random sampling design was used in this study in selecting the respondents. On the level of perception among the Manobo tribe, the Manobos agree on their belief in god as supported with the total average weighted mean ranging from 2.01 to 2.73 or agree.  They strongly agree to get involved in social gathering as evidenced with total weighted mean of 2.21 or agree.  They strongly agree on good aspiration as evidenced with average weighted mean of 2.71 or agree.  They agree on the family practices as supported with the average weighted mean of 2.45 or agree.  They strongly agree on good family upbringing accompanied with an average weighted mean of 2.57 or strongly agree.  They also strongly agree on how to treat visitors accompanied with an average weighted mean of 2.79 or strongly agree. On the living conditions, the Manobos rank 1 that they do not depend their main source of income but they work hard to have additional income for their family needs.  They also rank 1 that their house is made up of wood, Nipa and bamboos for the shelter of their family and the Manobo rank 1 that they usually used herbal for their natural medicine but they send the sick person to the hospital for the health of the family. On the social conditions, the Manobos strongly agree to establish a neighborhood relationship with an average weighted mean of 2.78 or strongly agree.  They also agree to establish kinship relationship and community relationship as indicated with an average weighted mean of 2.84 and 2.78 or strongly agree respectively. On the effect of perception on different aspects of life, belief in God, social; gathering, family practices, family upbringing and aspiration are best predictors in the financial condition of Manobo.  Aspiration, family practices, treating visitors, wedding practices and social gathering are best predictors in neighborhood relationship.  Wedding practices, treating visitors, aspiration, family practices, social gathering, family upbringing and belief in God as the best predictors in kinship relationship Family upbringing, aspiration, and family practices are best predictors in community relationship.

Addressing Linear Regression Models With Correlated Regressors: Some Package Development in R

Regression analysis is widely used in manyelds such as economics,nance, technology and social sciences. A linear regression model describes the relationship between dependent variable and one or more regressors. A problem named multicollinearity is the existence/presence of nearly linear dependency among regressors. The existence of severe multicollinearity questions the accuracy of the parameters estimate in a linear regression model, because the variance of the ordinary least square estimator (OLSE) would be large enough. Therefore, detection of multicollinearity can be considered asrst step for giving solution of this problem. There are several indicators (diagnostic measures) for the quanti cation of collinearity among regressors available in the literature. Widely used and the most suggested diagnostics are values of pair-wise correlations among regressors, overall R2, VIF and tolerance limit, eigenvalues, condition number and condition indices etc. However, there is no unique method that can detect and measure the existence and strength of multicollinearity in data. For remedy or reduction of collinearity among regressors, biased estimators are suggested such as the ridge and Liu estimators in literature and are alternative to the OLSE. These alternative methods also improve the accuracy of the parameter estimates of linear regression models. The biased methods resemble each other and are based on similar principals. In this study, we propose two new detection methods for indication of collinearity vi existence and developed 3 packages in R language namely mctest, lmridge and liureg. The package mctest computes already existing collinearity diagnostic measures and our proposed measures. We also compare existing and our proposed collinearity diagnostics measures for the detection of collinearity existence among regressors. Our proposed collinearity diagnostics not only perform well for simulated but also for real collinear data sets. For computation and detection of existence of collinearity mctest package can be used. The package contains functions omcdiag for computation of overall and imcdiag for individual collinearity diagnostics as described in Chapter 3, Section 3.5. For estimation and testing of ridge coe cients, the ridge package lmridge can be used to compute ridge coe cients, di erent existing biasing parameters available in literature and testing of ridge coe cients with 15 ridge related statistics such as R2, adjusted-R2, mean square error and e ective degrees of freedom etc. Similarly, estimation and testing of Liu coe cient can be done using package liureg package. It computes biasing parameters from (Liu, 1993) and the Liu related statistics. In addition, numerical comparisons between existing estimator of ridge and Liu are also done by using existing collinear data set from Hald (1952), Longley (1967) and Malinvaud (1968).