What's the smart grid buzz in 2011? Behind-the-scenes discussions yield fruitful harvest Kate Rowland | Feb 08, 2011 I did a lot of listening last week. One of the most-asked questions at any industry conference, participant to participant, is "what are you hearing?" DistribuTECH was no different. The answers this time, though, were far more disparate than two years ago, at the same conference, in the same venue, when the answers were clearly "stimulus funding" and "smart meters/AMI." Here's
Words: 863 - Pages: 4
Mgt 2070 Assignment 2 – Solutions 4.13 As you can see in the following table, demand for heart transplant surgery at Washington General Hospital has increased steadily in the past few years: |Year |1 |2 |3 |4 |5 |6 | |Heart Transplants |45 |50 |52 |56 |58 |? | The
Words: 1335 - Pages: 6
complete new graphical user interface to the existing S-PLUS programming environment. It allowed non-programming minded users to access the advanced visualization techniques and modern analysis methods of S-PLUS. As a result, S-PLUS has gained enormous popularity over the past years among applied statisticians and data analysts. Over the last three years the content of this book has been used for introductory courses on S-PLUS. This book is aimed at people who are (completely) new to S-PLUS. It covers
Words: 10252 - Pages: 42
consideration their attitudes, beliefs, and assumptions about College Physics. The study utilized the one-group pretest – posttest design in an experimental study. A Likert-type scale instrument was used as a data gathering instrument. The analysis of data was shown on the descriptive data analysis with the use of the frequency and percentage. The researchers utilized t- Test to determine the significant difference in the expectations of second year students enrolled in college physics before and after
Words: 1550 - Pages: 7
useful in collecting data to develop appropriate research questions, hypothesis, research design, and result reporting. This paper will discuss and describe the following elements: 0. Research problem and purpose 0. Significance, scope, magnitude, and feasibility of finding a solution to the issue, opportunity, or problem 0. Research question, hypothesis, and variables 0. Research design 0. Instrument you developed or selected 0. Sampling method 0. Overall data analysis approach 0. Result
Words: 1682 - Pages: 7
and have made good decisions and poor decisions along the way regarding Business Intelligence. Business Intelligence (BI) is a term that refers to a variety of software applications used to analyze an organization’s data. It is a discipline made up of several activities, including data mining, analytical processing, query and report writing. This paper will discuss two Business Intelligence case studies and lessons learned from the studies regarding creating, implementing, and using business intelligence
Words: 307 - Pages: 2
There are several ways that Data-Mining can be used. A useful way is through customer attrition, which includes companies. Companies should have a complete retention strategy, due to gathering new customers is costly. Being able to retain customers during a downfall, when that is happening people are looking for a lower cost alternative. Knowing why a customer is leaving is important. There are customer churn analysis and apprehending methods, and trend analysis. Along with the customer churn profiling
Words: 492 - Pages: 2
company and based on the problems that we have defined we came up with hypothesis which we have tested and analyzed to come up with the solution that this telecom company is in need of. The solutions were derived from the results of the various data analysis methods that are conducted on the SPSS. After deriving the results, the solution is provided to Viva to implement in order to over
Words: 5260 - Pages: 22
thinking critically, gathering information, and taking notes and then evaluating them. 3. What are your biggest challenges in doing research? . My biggest challenges in doing research are research paradigms, research designs, methods, and data analysis techniques. Moreover, Finding or collecting information, and using reliable resources. I take plenty of time reading and searching, but sometimes I miss some information that’s maybe important. Another challenge is choosing the right topic and
Words: 343 - Pages: 2
Evolution of Big Data Defining Big Data “Data-driven decision making, popularized in the 1980s and 1990s, has evolved into a vastly more sophisticated concept known as big data that relies on software approaches generally referred to as analytics”(Picciano, 2012). Big data is one of the great new frontiers of IT. Data is exploding so fast and the promise of deeper insights is so compelling that IT managers are highly motivated to turn big data into an asset that can
Words: 1224 - Pages: 5
