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    Data Preprocessing

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    IT433 Data Warehousing and Data Mining — Data Preprocessing — 1 Data Preprocessing • Why preprocess the data? • Descriptive data summarization • Data cleaning • Data integration and transformation • Data reduction • Discretization and concept hierarchy generation • Summary 2 Why Data Preprocessing? • Data in the real world is dirty – incomplete: lacking attribute values‚ lacking certain attributes of interest‚ or containing only aggregate data • e.g.‚ occupation=“ ”

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    Simulation N Modeling

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    relationships o Symbolic relationships Between the entities of the system. Measures of performance The model solved by mathematical methods such as differential calculus‚ probability theory‚ algebraic methods has the solution usually consists of one or more numerical parameters which are called measures of performance. 1.1 When Simulation is the Appropriate Tool • Simulation enables the study of and experimentation with the internal interactions of a complex system‚ or of a subsystem within a complex system.

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    Finance

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    QUANTITATIVE ANALYSIS APPROACHES TO QUALITATIVE DATA: WHY‚ WHEN AND HOW - Savitri Abeyasekera Statistical Services Centre‚ University of Reading‚ P.O. Box 240‚ Harry Pitt Building‚ Whiteknights Rd.‚ Reading RG6 6FN‚ UK. Phone 0118 931 8459‚ e-mail s.abeyasekera@rdg.ac.uk 1. Introduction In many research studies involving the use of participatory tools‚ much of the information gathered is of a qualitative nature. Some of this will contribute to addressing specific research questions‚ while

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    Statistics for Management

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    correlation and Regression 13. Business Forecasting 14. Time Series Analysis 15 . Index Numbers Indian B2B site for Manufacturers & Exporters Q: What’s the definition of Statistics ? A : Statistics are usually defined as: 1. A collection of numerical data that measure something. 2. The science of recording‚ organising‚ analysing and reporting quantitative information. Q: What are the different components of statistics ? A: There are four components as per Croxton & Cowden 1. Collection of

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    Number and Rs.

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    _____________Download from www.JbigDeaL.com Powered By © JbigDeaL____________ NUMERICAL APTITUDE QUESTIONS 1 (95.6x 910.3) ÷ 92.56256 = 9? (A) 13.14 (B) 12.96 (C) 12.43 (D) 13.34 (E) None of these 2. (4 86%of 6500) ÷ 36 =? (A) 867.8 (B) 792.31 (C) 877.5 (D) 799.83 (E) None of these 3. (12.11)2 + (?)2 = 732.2921 (A)20.2 (B) 24.2 (C)23.1 (D) 19.2 (E) None of these 4.576÷ ? x114=8208 (A)8 (B)7 (C)6 (D)9 (E) None of these 5. (1024—263—233)÷(986—764— 156) =? (A)9 (B)6

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    Design of Computers

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    conditional jumps‚ and the machine had a separate inpud/output unit. For more than ten years he received government funding for his project‚ which amounted to £17‚000.00‚ but eventually the Treasury lost confidence in Babbage. In Babbage’s time‚ numerical tables were calculated by humans who were called ’computers’‚ meaning "one who computes"‚ much as a conductor is "one who conducts". At Cambridge‚ he saw the high error-rate of this human-driven process and started his life’s work of trying to calculate

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    ACCT444 WK4 HW4 Mk

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    invoice was transposed and‚ as a result‚ charged to the wrong customer. By the time the error was found‚ the original customer was no longer in business. Recorded transactions exist Transactions are properly posted and summarized Key verification Check digit Reconciliation to

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    STATS TCO 1

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    POPULATION: The age of each resident in an apartment building EXAMPLE OF SAMPLE: The temperature in 4 state capitals out of 50 PARAMETER: is a numerical description of a population characteristic EXAMPLE OF PARAMETER: the 2182 students who accepted admission offers to Northwestern University in 2008 have an average SAT score of 1442 STATISTIC: is a numerical description of a sample characteristic EXAMPLE OF STATISTIC: a study of 6076 adults in public restrooms found that 23% did not wash their hands

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    SI Heat 4e Chap01 Lecture

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    Heat and Mass Transfer: Fundamentals & Applications Fourth Edition in SI Units Yunus A. Cengel‚ Afshin J. Ghajar McGraw-Hill‚ 2011 Chapter 1 INTRODUCTION AND BASIC CONCEPTS Mehmet Kanoglu University of Gaziantep Copyright © The McGraw-Hill Companies‚ Inc. Permission required for reproduction or display. Objectives • Understand how thermodynamics and heat transfer are related to each other. • Distinguish thermal energy from other forms of energy‚ and heat transfer from other forms of energy transfer

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    Chi Square

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    Chi-square requires that you use numerical values‚ not percentages or ratios. Then calculate 2 using this formula‚ as shown in Table B.1. Note that we get a value of 2.668 for 2. But what does this number mean? Here’s how to interpret the 2 value: 1. Determine degrees of freedom (df). Degrees of freedom can be calculated as the number of categories in the problem minus 1. In our example‚ there are two categories (green and yellow); therefore‚ there is I degree of freedom. 2. Determine a relative

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