MEAN SCORE Descriptive Statistics N Mean Std.Deviation Discount 196 1.38 .672 Gift Coupon 196 1.47 .603 Free tour 196 1.91 .929 Cash back 196 1.44 .634 Price 196 1.54 .753 Quality 196 1.44 .592 Quantity 196 1.58 .715 Varity 196 1.68 .609 Brand 196 1.66 .641 Durability 196 1.94 .732 Availability 196 2.04 .902 Promotion Scheme 196 2.24 .944 Advertisement 196 2.10 .871 Promotional scheme of Berger paint is very attractive. 196 1.99 .791
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Big data is the term for a collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications. The challenges include capture‚ curation‚ storage search‚ sharing‚ transfer‚ analysis and visualization. At multiple TERABYTES in size‚ the text and images of Wikipedia are a classic example of big data. As of 2012‚ limits on the size of data sets that
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Telecommunications Data Issues Telecommunications have played a big role in today’s generation. Without it‚ it may be impossible for us live in a technologically-advanced world. In full gratitude to the first inventors‚ we are now able to communicate to other people to the other part of the world‚ transact a business with business partners from other nations without going out of the country. Country to country negotiation has become easier and data can be accessible anywhere. Telecommunications data has been
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WEEK 1 WHAT ARE DATA STRUCTURES? WHAT ARE ALGORITHMS? REVIEW OF JAVA AND OOP ENCAPSULATION‚ INHERITANCE‚ POLYMORPHISM CLASSES METHOD INTERFACES DATA STRUCTURES In computer science‚ a data structure is a particular way of storing and organizing data in a computer so that it can be used efficiently. Different kinds of data structures are suited to different kinds of applications and some are highly specialized to certain tasks. For example‚ B-trees are particularly well-suited
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equation extended: towards conceptual clarity in the relationship between data‚ information and knowledge. European Journal of Information Systems‚ 2010(19)‚ 409-421. doi:10.1057/ejis.2010.25; published online 11 May 2010 Purpose (What are the objectives for writing the paper?): Provide a clear distinction between data‚ information and knowledge as it relates to information systems (IS) and the implications for IS related research. Several well-known theories are identified and exposed as reference
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Analyzing and Interpreting Data QNT/351 September 16‚ 2014 Analyzing and Interpreting Data BIMS management team has been facing a major dilemma of high turnover and extremely low employee morale. BIMS management team has asked Team B to help identify the main cause of the high turnover and low morale and propose an acceptable solution that will result in a decrease of both. Data Collection Conclusion In the past few months we at BIMS have learned‚ thru the drop in employees that the company’s
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in Canada or the entire country. Fast solution to the content problem must be found in order to expand into the United States. Figure out how to generate the database and how to pay for it. Find out if there were already databases that could be used to generate the content. Figure out the cost of hiring workers and expansion in other cities and calculate their financial projections and make the best option. Justifications: Apple had an early advantage into the app distribution
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to confidentiality. They are: • Data protection act 1998 • Access to personal files act 1987 • Access to medical records act 1990 The following have to follow legislation mentioned above: • Nurseries-private/government based/child minders/nannies • Hospitals-private/government funded • Schools-private/government funded • Doctor surgeries • Care homes • NHS Data protection act 1998 The Data protection act was developed to give
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http://hdl.handle.net/2451/31553 Data Science and Prediction Vasant Dhar Professor‚ Stern School of Business Director‚ Center for Digital Economy Research March 29‚ 2012 Abstract The use of the term “Data Science” is becoming increasingly common along with “Big Data.” What does Data Science mean? Is there something unique about it? What skills should a “data scientist” possess to be productive in the emerging digital age characterized by a deluge of data? What are the implications for business
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Statistics involves the development of methods and tests that are used to quantitatively define the variability inherent in data‚ the probability of certain outcomes‚ and the error and uncertainty associated with those outcomes. Some statistics are biased‚ some are based on opinions‚ and some are fabricated. A common misconception is that statistics provide a measure of proof that something is true. Instead‚ statistics provide a measure of the probability of observing a certain result. It is easy
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