An introduction to the analysis of the matrix

In general, the forces of competition are imposing a need for more effective decision making at all levels in organizations.

An introduction to the analysis of the matrix

Total unadjusted count 50 UFPs All of the functional components are analyzed in this way and added together to derive an Unadjusted Function Point count. This factor considers the system's technical and operational characteristics and is calculated by answering 14 questions.

Data Communications The data and control information used in the application are sent or received over communication facilities. Distributed Data Processing Distributed data or processing functions are a characteristic of the application within the application boundary.

Performance Application performance objectives, stated or approved by the user, in either response or throughput, influence or will influence the design, development, installation and support of the application.

Heavily Used Configuration A heavily used operational configuration, requiring special design considerations, is a characteristic of the application.

Transaction Rate The transaction rate is high and influences the design, development, installation and support. On-line Data Entry On-line data entry and control information functions are provided in the application.

End -User Efficiency The on-line functions provided emphasize a design for end-user efficiency. On-line Update The application provides on-line update for the internal logical files.

Complex Processing Complex processing is a characteristic of the application. Reusability The application and the code in the application have been specifically designed, developed and supported to be usable in other applications. Installation Ease Conversion and installation ease are characteristics of the application.

Operational Ease Operational ease is a characteristic of the application. Effective start-up, backup and recovery procedures were provided and tested during the system test phase. Multiple Sites The application has been specifically designed, developed and supported to be installed at multiple sites for multiple organizations.

Facilitate Change The application has been specifically designed, developed and supported to facilitate change. Each of these factors is scored based on their influence on the system being counted.

This calculation provides us with the Adjusted Function Point count. The workshop approach allows the counter to develop a representation of the application from a functional perspective and educate the participants about function points.

Function point counting can be accomplished with minimal documentation. However, the accuracy and efficiency of the counting improves with appropriate documentation. Examples of appropriate documentation are: Design specifications Data requirements Internal and External Description of user interfaces Function point counts are calculated during the workshop and documented with both a diagram that depicts the application and worksheets that contain the details of each function discussed.

Benefits of Function Point Analysis Organizations that adopt Function Point Analysis as a software metric realize many benefits including: Each of these is discussed below. Estimating software projects is as much an art as a science.

While there are several environmental factors that need to be considered in estimating projects, two key data points are essential. The first is the size of the deliverable. The second addresses how much of the deliverable can be produced within a defined period of time.

Size can be derived from Function Points, as described above. The second requirement for estimating is determining how long it takes to produce a function point. This delivery rate can be calculated based on past project performance or by using industry benchmarks.

Productivity measurement is a natural output of Function Points Analysis. Since function points are technology independent they can be used as a vehicle to compare productivity across dissimilar tools and platforms.

More importantly, they can be used to establish a productivity rate i. Once productivity rates are established they can be used for project estimating as described above and tracked over time to determine the impact continuous process improvement initiatives have on productivity.

In addition to delivery productivity, function points can be used to evaluate the support requirements for maintaining systems. In this analysis, productivity is determined by calculating the number of function points one individual can support for a given system in a year i.

When compared with other systems, these rates help to identify which systems require the most support. The resulting analysis helps an organization develop a maintenance and replacement strategy for those systems that have high maintenance requirements.

Managing Change of Scope for an in-process project is another key benefit of Function Point Analysis. Once a project has been approved and the function point count has been established, it becomes a relatively easy task to identify, track and communicate new and changing requirements.

As requests come in from users for new displays or capabilities, function point counts are developed and applied against the rate.

This result is then used to determine the impact on budget and effort.1.

An introduction to the analysis of the matrix

INTRODUCTION A short introduction to Social Network Analysis. A network is made of two components: a list of the actors composing the network, and a list of the relations (the interactions between actors).As part of a mathematical object, actors will then be called vertices (nodes, in Gephi), and relations will be denoted as tiles (edges, in Gephi).

Decision making under risk is presented in the context of decision analysis using different decision criteria for public and private decisions based on decision criteria, type, and quality of available information together with risk assessment.

A matrix with m rows and n columns is called an m × n matrix or m-by-n matrix, while m and n are called its dimensions. For example, the matrix A above is a 3 × 2 matrix. Matrices with a single row are called row vectors, and those with a single column are called column vectors.

1 Introduction to GIS (Basics, Data, Analysis) & Case Studies 13th May Content • Introduction to GIS • Data concepts • Data input • Analysis • Applications – selected examples.

Introduction and history. The biplot was introduced by K. Ruben Gabriel (). Gower and Hand () wrote a monograph on biplots. Yan and Kang () described various methods which can be used in order to visualize and interpret a biplot.

Long considered to be a classic in its field, this was the first book in English to include three basic fields of the analysis of matrices - symmetric matrices and quadratic forms, matrices and differential equations, and positive matrices and their use in probability theory and mathematical economics/5(4).

Biplot - Wikipedia