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    Big Data

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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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    Data Analys

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    of variables Qualitative Quantitative • Reliability and Validity • Hypothesis Testing • Type I and Type II Errors • Significance Level • SPSS • Data Analysis Data Analysis Using SPSS Dr. Nelson Michael J. 2 Variable • A characteristic of an individual or object that can be measured • Types: Qualitative and Quantitative Data Analysis Using SPSS Dr. Nelson Michael J. 3 Types of Variables • Qualitative variables: Variables which differ in kind rather than degree • Measured

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    Data Interpretation

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    Interpreting your data is a process that involves answering a series of questions about the research. We suggest the following steps: 1) Review and interpret the data "in-house" to develop preliminary findings‚ conclusions‚ and recommendations. 2) Review the data and your interpretation of it with an advisory group or technical committee. This group should involve local‚ regional‚ and state resource people who are familiar with monitoring and with your product. They can verify‚ add to‚ or

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    Data Processing

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    1. Data Processing- is any process that a computer program does to enter data and‚ summarize‚ analyze or otherwise convert data into usable information. The process may be automated and run on a computer. It involves recording‚ analyzing‚ sorting‚ summarizing‚ calculating‚ disseminating and storing data. Because data are most useful when well-presented and actually informative‚ data-processing systems are often referred to as information systems. Nevertheless‚ the terms are roughly synonymous‚ performing

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    Data Warehouse

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    Data Warehouse Concepts and Design Contents Data Warehouse Concepts and Design 1 Abstract 2 Abbreviations 2 Keywords 3 Introduction 3 Jarir Bookstore – Applying the Kimball Method 3 Summary from the available literature and Follow a Proven Methodology: Lifecycle Steps and Tracks 4 Issues and Process involved in Implementation of DW/BI system 5 Data Model Design 6 Star Schema Model 7 Fact Table 10 Dimension Table: 11 Design Feature: 12 Identifying the fields from facts/dimensions: MS: 12 Advanced

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    Data Description

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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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    Statistics and Data

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    Definition: Statistics is the study of the collection‚ organization‚ analysis‚ interpretation and presentation of data. It deals with all aspects of this‚ including the planning of data collection in terms of the design of surveys and experiments. A statistician is someone who is particularly well-versed in the ways of thinking necessary for the successful application of statistical analysis. Such people have often gained experience through working in any of a wide number of fields. Some

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    data communication

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    What is Data Communications? Next Topic | TOC The distance over which data moves within a computer may vary from a few thousandths of an inch‚ as is the case within a single IC chip‚ to as much as several feet along the backplane of the main circuit board. Over such small distances‚ digital data may be transmitted as direct‚ two-level electrical signals over simple copper conductors. Except for the fastest computers‚ circuit designers are not very concerned about the shape of the conductor or

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    Data mining

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    Data Mining Project – Dogs Race Prediction Motivation Gambling is very popular in the Republic of Ireland‚ weather is online or not‚ more people are joining gambling communities formed all over the Island of Ireland. The majority of these communities are involved in horse races related gambling and other sports‚ but there is a significant amount of people dedicated to dogs races. This is a multimillion Euro industry developed on-line and live or face to face. Objective There are many websites

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    Data Anomalies

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    Data Anomalies Normalization is the process of splitting relations into well-structured relations that allow users to inset‚ delete‚ and update tuples without introducing database inconsistencies. Without normalization many problems can occur when trying to load an integrated conceptual model into the DBMS. These problems arise from relations that are generated directly from user views are called anomalies. There are three types of anomalies: update‚ deletion and insertion anomalies. An update anomaly

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