TYPES OF DATA AND COMPONENTS OF DATA STRUCTURES Data types 1. Primitive: is a data type provided by a programming language as a basic building block 2. Composite: is any data type which can be constructed in a program using its programming language’s primitive data types and other composite types 3. Abstract: is a mathematical model for a certain class of data structures that have similar behavior; or for certain data types of one or more programming languages that have similar semantics
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PRINCIPLES OF DATA QUALITY Arthur D. Chapman1 Although most data gathering disciples treat error as an embarrassing issue to be expunged‚ the error inherent in [spatial] data deserves closer attention and public understanding …because error provides a critical component in judging fitness for use. (Chrisman 1991). Australian Biodiversity Information Services PO Box 7491‚ Toowoomba South‚ Qld‚ Australia email: papers.digit@gbif.org 1 © 2005‚ Global Biodiversity Information Facility Material
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Research methods: Data analysis G Qualitative analysis of data Recording experiences and meanings Distinctions between quantitative and qualitative studies Reason and Rowan’s views Reicher and Potter’s St Paul’s riot study McAdams’ definition of psychobiography Weiskrantz’s study of DB Jourard’s cross-cultural studies Cumberbatch’s TV advertising study A bulimia sufferer’s diary G Interpretations of interviews‚ case studies‚ and observations Some of the problems involved in drawing
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Chapt 10 # 42 H0: game length is >= 3.5 hours Ha: game length is < 3.5 hours mean = 2.9553 stdev = 0.5596 Get the t test statistic: t = (x-mu)/(stdev/sqrt(N)) t = (2.9553-3.5)/(0.5596/sqrt(17)) t = -4.0133 Get the critical value for df = N-1 = 16‚ one tail‚ alpha is 0.05: -1.7459 Since our test statistic is much lower than the critical value‚ we reject the null hypothesis. There is enough evidence to conclude that games are shorter than 3.50 hours. Chapt 11 # 58 The amount
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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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Time Elapsed | 1 hour‚ 17 minutes out of 2 hours. | Instructions | This quiz consist of 20 multiple choice questions. The first 10 questions cover the material in Chapter 1. The second 10 questions cover the material in Chapter 2. Be sure you are in the correct Chapter when you take the quiz. | * Question 1 2 out of 2 points | | | An area of finance that refers to the physical locations or electronic forums that facilitate the flow of funds among investors‚ businesses‚ and governments
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study: MBA Course Title: Marketing Research Course code: MBA 763 Assignment: Secondary Data Mat Number: 74168 Name: Abiona Timothy Olufemi What is Data Data is a collection of facts‚ such as numbers‚ words‚ measurements‚ observations or even just descriptions of things. 1.Information in raw or unorganized form (such as alphabets‚ numbers‚ or symbols) that refer to‚ or represent‚ conditions‚ ideas‚ or objects. Data is limitless and present everywhere in the universe. See also information and knowledge
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Data migration • Data migration is the process of transferring data between storage types‚ formats‚ or computer systems. • Data migration is usually performed programmatically to achieve an automated migration‚ freeing up human resources from tedious tasks. • It is required when organizations or individuals change computer systems or upgrade to new systems. • To achieve an effective data migration procedure‚ data on the old system is mapped to the new system providing a design
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Data Preprocessing 3 Today’s real-world databases are highly susceptible to noisy‚ missing‚ and inconsistent data due to their typically huge size (often several gigabytes or more) and their likely origin from multiple‚ heterogenous sources. Low-quality data will lead to low-quality mining results. “How can the data be preprocessed in order to help improve the quality of the data and‚ consequently‚ of the mining results? How can the data be preprocessed so as to improve the efficiency and ease
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Big Data Management: Possibilities and Challenges The term big data describes the volumes of data generated by an enterprise‚ including Web-browsing trails‚ point-of-sale data‚ ATM records‚ and other customer information generated within an organization (Levine‚ 2013). These data sets can be so large and complex that they become difficult to process using traditional database management tools and data processing applications. Big data creates numerous exciting possibilities for organizations‚
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