1 CIPD unit 4DEP - Version 2 18.03.10 Unit title Developing Yourself as an Effective Human Resources or Learning and Development Practitioner Level 4 1 Credit value 4 Unit code 4DEP Unit review date Sept. 2011 Purpose and aim of unit The CIPD has developed a map of the HR profession (HRPM) that describes the knowledge‚ skills and behaviours required by human resources (HR) and learning and development (L&D) professionals. This unit is designed to enable the learner
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Table of Contents 1. VARIABLES- QUALITATIVE AND QUANTITATIVE......................3 1.1 Qualitative Data (Categorical Variables or Attributes) ........................... 3 1.2 Quantitative Data............................................................................................... 4 DESCRIPTIVE STATISTICS.................................................6 2.1 Sample Data versus Population Data ................................................................... 6 2.2 Parameters and Statistics
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ITE 221 – Project#1 – Data Representation http://msdn.microsoft.com/en-us/library/d11h6832%28v=VS.71%29.aspx Class library of the .NET Framework for Microsoft. 1. What is a data structure? A data structure is a related group of primitive data elements organized for some type of common processing and is defined and manipulated in software. 2. What is a library? A library contains resources for developing software. These resources could be pre-written code‚ subroutines‚ classes‚ values
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WORLD DATA CLUSTERING ADEWALE .O . MAKO DATA MINING INTRODUCTION: Data mining is the analysis step of knowledge discovery in databases or a field at the intersection of computer science and statistics. It is also the analysis of large observational datasets to find unsuspected relationships. This definition refers to observational data as opposed to experimental data. Data mining typically deals with data that has already been collected for some purpose or the other than the data mining
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Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific
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Data Mining: What is Data Mining? Overview Generally‚ data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue‚ cuts costs‚ or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles‚ categorize it‚ and summarize the relationships identified
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1) ________ is data that has been organized or presented in a meaningful fashion. 1) _______ A) A number B) Information C) A symbol D) A character 2) Which of the following is NOT one of the four major data-processing functions of a computer? 2) _______ A) storing the data or information B) gathering data C) analyzing the data or information D) processing data into information
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LECTURE 1 DATA TYPES Our interactions (inputs and outputs) of a program are treated in many languages as a stream of bytes. These bytes represent data that can be interpreted as representing values that we understand. Additionally‚ within a program we process this data that can be interpreted as representing values that we understand. Additionally‚ within a program we process this data in various way such as adding them up or sorting them. This data comes in different forms. Examples include: your
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Master Thesis Electrical Engineering November 2011 Security Techniques for Protecting Data in Cloud Computing Venkata Sravan Kumar Maddineni Shivashanker Ragi School of Computing Blekinge Institute of Technology SE - 371 79 Karlskrona Sweden i This thesis is submitted to the School of Computing at Blekinge Institute of Technology in partial fulfillment of the requirements for the degree of Master of Science in Software Engineering. The thesis is equivalent to 40 weeks of full time studies.
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ict policy Data Protection ICT/DPP/2010/10/01 1. Policy Statement 1.1. Epping Forest District Council is fully committed to compliance with the requirements of the Data Protection Act 1998 which came into force on the 1st March 2000. 1.2. The council will therefore follow procedures that aim to ensure that all employees‚ elected members‚ contractors‚ agents‚ consultants‚ partners or other servants of the council who have access to any personal data held by or on behalf of the
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