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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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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averages and variations‚ normal probability distributions‚ sampling distributions‚ confidence intervals and testing statistical hypotheses. The emphasis of the course will be on the proper use of statistical techniques and their implementation rather than on mathematical proofs. (Prerequisite: MATH110 formerly MA112). Table of Contents Course Scope | Successful completion of this course will provide you with a working knowledge of the principles of statistics and enable you to solve problems involving
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COMPLEXITY MEASURES IN MANUFACTURING SYSTEMS Alberto F. De Toni‚ Alessio Nardini‚ Fabio Nonino‚ Gianluca Zanutto Laboratory of Management Engineering‚ Department of Electrical‚ Management and Mechanical Engineering‚ University of Udine‚ Via delle Scienze 208 33100 Udine (UD)‚ Italy Corresponding Author: Gianluca Zanutto Office: (+39) 0432 55 82 96 Fax: (+39) 0432 55 82 51 e-mail: zanutto@uniud.it 1 Abstract This study analyzes the most widewpread methodologies available in literature
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Chapter 3 Data Description 3-1 Measures of Central Tendency ( page 3-3) Measures found using data values from the entire population are called: parameter Measures found using data values from samples are called: statistic A parameter is a characteristic or measure obtained using data values from a specific population. A statistic is a characteristic or measure obtained using data values from a specific sample. The Measures of Central Tendency are: • The Mean • The
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Data collection is any process of preparing and collecting data‚ for example‚ as part of a process improvement or similar project. The purpose of data collection is to obtain information to keep on record‚ to make decisions about important issues‚ or to pass information on to others. Data are primarily collected to provide information regarding a specific topic. Data collection usually takes place early on in an improvement project‚ and is often formalized through a data collection plan which often
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Handling Consumer Data Introduction When I visit my local Caltex Woolworths petrol station on “cheap fuel Wednesday” to cash in the 8c per litre credit that my Wife earned the previous Friday buying the groceries with our “Everyday Rewards” card‚ I did not‚ until researching this report‚ have any clue as to the contribution I was making to a database of frightening proportions and possibilities… nor that‚ when I also “decide” to pick up the on-sale‚ strategically-placed 600mL choc-milk‚ I am
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Introduction to Data Mining Assignment 1 Ex1.1 what is data mining? (a) Is it another hype? Data mining is Knowledge extraction from data this need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. So‚ data mining definitely is not another hype it can be viewed as the result of the natural evolution of information technology. (b) Is it a simple transformation of technology developed
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Lecture Notes 1 Data Modeling ADBMS Lecture Notes 1: Prepared by Engr. Cherryl D. Cordova‚ MSIT 1 • Database: A collection of related data. • Data: Known facts that can be recorded and have an implicit meaning. – An integrated collection of more-or-less permanent data. • Mini-world: Some part of the real world about which data is stored in a database. For example‚ student grades and transcripts at a university. • Database Management System (DBMS): A software package/ system to facilitate
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SMS CUSAT Reading Material on Data Mining Anas AP & Alex Titty John • What is Data? Data is a collection of facts and information or unprocessed information. Example: Student names‚ Addresses‚ Phone Numbers etc. • What is a Database? A structured set of data held in a computer which is accessible in various ways. Example: Electronic Address Book‚ Phone Book. • What is a Data Warehouse? The electronic storage of large amount of data by business. Concept originated in
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