RUAHA UNIVERSITY COLLEGE (RUCO) (A constituent college of the St. Augustine University of Tanzania) FACULTY OF BUSINESS AND MANAGEMENT SCIENCE MASTER OF BUSSINESS ADMINISTRATION (MBA) COURSE: BUSINESS RESEARCH METHODOLOGY COURCE CODE: RMB 604 NATURE OF ASSIGNMENT: INDIVIDUAL ASSIGNMENT COURSE INSTRUCTOR: DR. CHALU. NAME OF STUDENT
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Queenie 1097300104 E5B Data Analysis First Part Personal information: including the participants’ gender‚ age‚ educational background‚ marital status and monthly income. Gender As Figure 1 showed‚ there were 45% of female participants and 55% of male. The numbers of the participants of each gender were very close. Age The respondents were all my friends on Facebook; as the result‚ the majority (73%) of their age was in the range of 16-20‚ as seen in Figure 2. Figure 1: Gender
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(3995+L+11*Q) There are three variables in this equation‚ with the assumption; this model is realistic enough‚ if I was Sanjay‚ I will consider what the shape of the probability distribution of X is‚ and the measurement of this distribution to make risk analysis. a). Without considering the partnership opportunity‚ to solve the case‚ we run a Crystal Ball simulation with 1000 trials. The assumption variables are P‚ Q‚ and L‚ and the forecast variable is X. We found that Sanjay’s sample mean monthly salary
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descriptive essay on gregory and lather and nothing else Our lives are affected by our decisions. “Gregory” by Panos Ioannides and “Lather and Nothing Else” by Hernando Tellez both demonstrate dilemmas throughout the stories. It is observed that while decision making‚ every aspect and its outcome should be considered ad it is to be remembered that there are always options open and not every problem has an ultimatum. Ioannides and Tellez both talk about how altered our decisions
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Research Project - Data Protection Data can be collected by organisations such as the websites we use daily‚ such as Facebook and Twitter. They have our information such as our age‚ date of birth‚ home address and other personal information which we would not share with strangers‚ and it is their job to protect that data‚ so that it doesn’t get into the wrong hands‚ such as scammers. Organisations may collect information from you in a number of ways‚ over the internet‚ over the phone‚ or also
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DataBig Data and Future of Data-Driven Innovation A. A. C. Sandaruwan Faculty of Information Technology University of Moratuwa chanakasan@gmail.com The section 2 of this paper discuss about real world examples of big data application areas. The section 3 introduces the conceptual aspects of Big Data. The section 4 discuss about future and innovations through big data. Abstract: The promise of data-driven decision-making is now being recognized broadly‚ and there is growing enthusiasm
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Crime Data Comparison Comparing similar crimes‚ in metropolitan area such as Phoenix and Dallas. The FBI Uniform Crime Report (UCR) data shows in 2009 Phoenix had 76 reported murders‚ and Dallas with 86. Dallas with a lower population number of 1‚290‚266 had higher murder rate‚ Phoenix with population of 1‚597‚397 reported in 2009. Reported murder rates dropped in both areas in 2010‚ Dallas with 73‚ and Phoenix with a reported 50. “National reports a decrease of 6.2 percent of violent crimes during
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Outline Introduction Distributed DBMS Architecture Distributed Database Design Distributed Query Processing Distributed Transaction Management Data Replication Consistency criteria Update propagation protocols Parallel Database Systems Data Integration Systems Web Search/Querying Peer-to-Peer Data Management Data Stream Management Distributed & Parallel DBMS M. Tamer Özsu Page 6.1 Acknowledgements Many of these slides are from notes prepared by Prof. Gustavo
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Data mining and warehousing and its importance in the organization Data Mining Data mining 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. Technically‚ data
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Data mining Data mining is simply filtering through large amounts of raw data for useful information that gives businesses a competitive edge. This information is made up of meaningful patterns and trends that are already in the data but were previously unseen. The most popular tool used when mining is artificial intelligence (AI). AI technologies try to work the way the human brain works‚ by making intelligent guesses‚ learning by example‚ and using deductive reasoning. Some of the more popular
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