Cpk index estimation using data transformation

1995 ◽  
Vol 29 (1-4) ◽  
pp. 55-58 ◽  
Author(s):  
Luis Armando Rosas Rivera ◽  
Norma F. Hubele ◽  
Frederick P. Lawrence
Keyword(s):  
Data Transformation ◽  
Using Data ◽  
Index Estimation

scholarly journals An internal evaluation of higher education curriculum using data transformation model

2020 ◽  
Vol 10 (2) ◽  
pp. 1-9
Author(s):  
Michael Bobias Cahapay
Keyword(s):  
Higher Education ◽  
Data Transformation ◽  
Transformation Model ◽  
Data Sets ◽  
Education Curriculum ◽  
Evaluation Theory ◽  
Internal Evaluation ◽  
Higher Education Curriculum ◽  
Mixed Method Design ◽  
Using Data

A curriculum does not exist in a void; internal members play a key role in responding to the different forces that continually shape it. One of the approaches to evaluation is through internal evaluation from the perspective of the inside members who work with the curriculum. However, the internal evaluation may pose restricted evaluation due to the innate subjective human judgment. Considering these contexts, this paper performed a pilot internal evaluation of a selected aspect of a higher education curriculum using a triangulation mixed method design called the data transformation model. Based on the results, the evaluation using the data transformation model probed important points of agreement and discrepancy in the data sets. The implications for evaluation theory and curriculum practice are discussed. It is suggested that an extension of the current formative internal evaluation continuing the tradition of data transformative model but progressively focusing on larger aspects of the curriculum should be further conducted.

scholarly journals A Method for the Development of Dynamic Site Index Models Using Height–Age Data from Temporal Sample Plots

Forests ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 542
Author(s):  
Jarosław Socha ◽  
Luiza Tymińska-Czabańska
Keyword(s):  
Forest Management ◽  
Site Index ◽  
Height Growth ◽  
Strategic Decisions ◽  
Growth Trend ◽  
Potential Productivity ◽  
Forest Sites ◽  
Using Data ◽  
Temporal Sample ◽  
Index Estimation

Knowledge of the potential productivity of forest sites is fundamental for making strategic decisions in forest management. Site productivity is usually evaluated using the site index, and therefore the development of site index models is one of the crucial tasks in forest research and forest management. This research aims to develop an effective method for building top-growth and site index models using data from temporary sample plots (TSP). Exploiting the advantages of the generalised algebraic difference approach (GADA), the proposed method overcomes the limitations of the guide curve method that has been to date used in site index modelling using TSPs data and allows to obtain only a set of anamorphic site index curves. The proposed approach enables the construction of dynamic site index models with polymorphism and variable asymptotes. Such models better reflect local, site-specific height growth trajectories and therefore allow more appropriate site index estimation. We tested the proposed method using data collected from 5105 temporary sample plots in Poland. Our results indicate that growth trend estimates using height–age measurements of TSPs may be valuable data for modelling top height growth. For these reasons, the proposed method can be very useful in forest management.

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