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Examining Distributions
 
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Unit 1, Part 1 Quantitative Data & Categorical Data Descritptive Statistical Methods
Views: 3372 Robert Emrich
Math Antics - Mean, Median and Mode
 
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Learn More at mathantics.com Visit http://www.mathantics.com for more Free math videos and additional subscription based content!
Views: 1269569 mathantics
Statistics I
 
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Download the Show Notes: http://www.mindset.co.za/learn/sites/files/LXL2013/LXL_Gr11Mathematics_30_Statistics_30Sept.pdf In this live Grade 11 Maths show we take a close look at Statistics I. In this lesson we revise how to represent data using histrograms and frequency polygons. We analyse data by examining box and whisker plots & finally we revise measures of central tendency. Visit the Learn Xtra Website: http://www.learnxtra.co.za View the Learn Xtra Live Schedule: http://www.learnxtra.co.za/live Join us on Facebook: http://www.facebook.com/learnxtra Follow us on Twitter: http://twitter.com/learnxtra ( E00200242 )
Views: 28523 Mindset Learn
Using Excel to illustrate a uniform probability distribution
 
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This is for Data Management courses where we study uniform PDs as one kind of many probability distributions. We are using an Excel simulation to show that dice rolls give a uniform probability distributions by examining their relative frequencies ... ( or *are* they uniform...?)
Views: 18941 Paul King
How to Analyze Satisfaction Survey Data in Excel with Countif
 
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Purchase the spreadsheet (formulas included!) that's used in this tutorial for $5: https://gum.co/satisfactionsurvey ----- Soar beyond the dusty shelf report with my free 7-day course: https://depictdatastudio.teachable.com/p/soar-beyond-the-dusty-shelf-report-in-7-days/ Most "professional" reports are too long, dense, and jargony. Transform your reports with my course. You'll never look at reports the same way again.
Views: 397880 Ann K. Emery
How to calculate interquartile range IQR | Data and statistics | 6th grade | Khan Academy
 
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Learn how to calculate the interquartile range, which is a measure of the spread of data in a data set. Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-data-statistics/cc-6th/e/calculating-the-interquartile-range--iqr-?utm_source=YT&utm_medium=Desc&utm_campaign=6thgrade Watch the next lesson: https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-data-statistics/cc-6-mad/v/mean-absolute-deviation?utm_source=YT&utm_medium=Desc&utm_campaign=6thgrade Missed the previous lesson? https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-data-statistics/cc-6th-box-whisker-plots/v/interpreting-box-plots?utm_source=YT&utm_medium=Desc&utm_campaign=6thgrade Grade 6th on Khan Academy: By the 6th grade, you're becoming a sophisticated mathemagician. You'll be able to add, subtract, multiply, and divide any non-negative numbers (including decimals and fractions) that any grumpy ogre throws at you. Mind-blowing ideas like exponents (you saw these briefly in the 5th grade), ratios, percents, negative numbers, and variable expressions will start being in your comfort zone. Most importantly, the algebraic side of mathematics is a whole new kind of fun! And if that is not enough, we are going to continue with our understanding of ideas like the coordinate plane (from 5th grade) and area while beginning to derive meaning from data! (Content was selected for this grade level based on a typical curriculum in the United States.) About Khan Academy: Khan Academy offers practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. We tackle math, science, computer programming, history, art history, economics, and more. Our math missions guide learners from kindergarten to calculus using state-of-the-art, adaptive technology that identifies strengths and learning gaps. We've also partnered with institutions like NASA, The Museum of Modern Art, The California Academy of Sciences, and MIT to offer specialized content. For free. For everyone. Forever. #YouCanLearnAnything Subscribe to Khan Academy‰Ûªs 6th grade channel: https://www.youtube.com/channel/UCnif494Ay2S-PuYlDVrOwYQ?sub_confirmation=1 Subscribe to Khan Academy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 439946 Khan Academy
Biased Data #43
 
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examining a question that analyzing data collection techniques
Views: 601 shaunteaches
SPSS: Analyzing Subsets and Groups
 
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Instructional video on how to analyze subsets and groups of data using SPSS, statistical analysis and data management software. For more information, visit SSDS at https://ssds.stanford.edu.
Power law distributions in entrepreneurship: Implications for theory and research
 
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A long-held assumption in entrepreneurship research is that normal (i.e., Gaussian) distributions characterize variables of interest for both theory and practice. We challenge this assumption by examining more than 12,000 nascent, young, and hyper-growth firms. Results reveal that variables which play central roles in resource-, cognition-, action-, and environment-based entrepreneurship theories exhibit highly skewed power law distributions, where a few outliers account for a disproportionate amount of the distribution's total output. Our results call for the development of new theory to explain and predict the mechanisms that generate these distributions and the outliers therein. We offer a research agenda, including a description of non-traditional methodological approaches, to answer this call.
Views: 253 Elsevier Journals
Median Polish - Exploratory Data Analysis
 
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[NOTE: Good CC/Subtitles Added] Median Polish is an Exploratory Data Analysis technique for analyzing two-way tables. This video shows a step-by-step example of working the Median Polish on a simple 3x3 two-way table: -15 4 1 6 16 30 -5 4 -12 Here is a simple R program that will create 3x3 two-way tables for you to practice with, and the median polish results generated by R: tbl = matrix(data=as.integer(runif(9) * 10), nrow=3, ncol=3) tbl medpolish(tbl)
Views: 5048 Timothy Chen Allen
What is GEOSPATIAL ANALYSIS? What does GEOSPATIAL ANALYSIS mean? GEOSPATIAL ANALYSIS meaning
 
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What is GEOSPATIAL ANALYSIS? What does GEOSPATIAL ANALYSIS mean? GEOSPATIAL ANALYSIS meaning - GEOSPATIAL ANALYSIS definition - GEOSPATIAL ANALYSIS explanation. Source: Wikipedia.org article, adapted under https://creativecommons.org/licenses/by-sa/3.0/ license. SUBSCRIBE to our Google Earth flights channel - https://www.youtube.com/channel/UC6UuCPh7GrXznZi0Hz2YQnQ Geospatial analysis, or just spatial analysis, is an approach to applying statistical analysis and other analytic techniques to data which has a geographical or spatial aspect. Such analysis would typically employ software capable of rendering maps processing spatial data, and applying analytical methods to terrestrial or geographic datasets, including the use of geographic information systems and geomatics. Geographic information systems (GIS), which is a large domain that provides a variety of capabilities designed to capture, store, manipulate, analyze, manage, and present all types of geographical data, and utilizes geospatial analysis in a variety of contexts, operations and applications. Geospatial analysis, using GIS, was developed for problems in the environmental and life sciences, in particular ecology, geology and epidemiology. It has extended to almost all industries including defense, intelligence, utilities, Natural Resources (i.e. Oil and Gas, Forestry ... etc.), social sciences, medicine and Public Safety (i.e. emergency management and criminology), disaster risk reduction and management (DRRM), and climate change adaptation (CCA). Spatial statistics typically result primarily from observation rather than experimentation. Vector-based GIS is typically related to operations such as map overlay (combining two or more maps or map layers according to predefined rules), simple buffering (identifying regions of a map within a specified distance of one or more features, such as towns, roads or rivers) and similar basic operations. This reflects (and is reflected in) the use of the term spatial analysis within the Open Geospatial Consortium (OGC) “simple feature specifications”. For raster-based GIS, widely used in the environmental sciences and remote sensing, this typically means a range of actions applied to the grid cells of one or more maps (or images) often involving filtering and/or algebraic operations (map algebra). These techniques involve processing one or more raster layers according to simple rules resulting in a new map layer, for example replacing each cell value with some combination of its neighbours’ values, or computing the sum or difference of specific attribute values for each grid cell in two matching raster datasets. Descriptive statistics, such as cell counts, means, variances, maxima, minima, cumulative values, frequencies and a number of other measures and distance computations are also often included in this generic term spatial analysis. Spatial analysis includes a large variety of statistical techniques (descriptive, exploratory, and explanatory statistics) that apply to data that vary spatially and which can vary over time. Some more advanced statistical techniques include Getis-ord Gi* or Anselin Local Moran's I which are used to determine clustering patterns of spatially referenced data. Geospatial analysis goes beyond 2D and 3D mapping operations and spatial statistics. It includes: Surface analysis —in particular analysing the properties of physical surfaces, such as gradient, aspect and visibility, and analysing surface-like data “fields”; Network analysis — examining the properties of natural and man-made networks in order to understand the behaviour of flows within and around such networks; and locational analysis. GIS-based network analysis may be used to address a wide range of practical problems such as route selection and facility location (core topics in the field of operations research, and problems involving flows such as those found in hydrology and transportation research. In many instances location problems relate to networks and as such are addressed with tools designed for this purpose, but in others existing networks may have little or no relevance or may be impractical to incorporate within the modeling process....
Views: 2959 The Audiopedia
Pressure Management: Industry Practices and Monitoring Procedures
 
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04/10/2014 Water Research Foundation Webcast. ​Most systems tend to operate at much higher pressure than needed, resulting in increased energy use, increased non-revenue water loss, and excessive main breaks. Project #4321, Pressure Management: Industry Practices and Monitoring Procedures developed guidance on best practices and cost/benefits of implementing an optimized pressure management program. The project included an analysis of a year-long pressure monitoring program from 22 utilities. This Webcast will focus on these results and a survey of pressure management practices, examining the case study examples and providing recommendations to improve pressure management in drinking water distribution systems. The final deliverables for this project are available on the website.
Data Transformation for Positively and Negatively Skewed Distributions in SPSS
 
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This video demonstrates how to transform data that are positively or negatively skewed using SPSS. Concepts such as log10 transformation, determining skewness, reflection, adjusting for zeros, and adjusting for negative numbers are described.
Views: 83268 Dr. Todd Grande
EXPERT INSIGHT at TMF: Digital Integration - Standardizing Event Data Collection and Management
 
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Neural Technologies' VP of Marketing Claus Nielsen delivers a seminar to Operators at TM Forum's Digital Transformation Asia 2018. - Understanding the importance of standardizing event data collection and management to facilitate faster and easier event data distribution/consumptions by downstream applications & partners - Examining the challenges involved in: Event Data Collection & Distribution Event Data Life Cycle Management Event Data Driven Decision Making - The Introduction of the Event Data Lake (ELD) Platform - How are various stakeholders working together to drive standardization?
Edge Data Management Solutions for Internet of Things (IoT)
 
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The key challenges preventing IoT initiatives to be successful are the inability to capture and process data directly from thousands of edge devices as well as the lack of operational visibility and control of the edge. Dinesh Chandrasekhar, Director of Product Marketing for Data-in-Motion at Cloudera, talks about solutions designed to solve these IoT challenges.
Views: 572 Cloudera, Inc.
Exploring GIS: Why spatial is special?
 
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An overview of the spatial thinking process in geographic information systems and science. The presentation includes the spatial thinking questions that a GIS can answer.
Views: 2854 GIS VideosTV
Percentiles and Quartiles
 
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statisticslectures.com - where you can find free lectures, videos, and exercises, as well as get your questions answered on our forums!
Views: 436099 statslectures
STUDY EVERYTHING IN LESS TIME! 1 DAY/NIGHT BEFORE EXAM | HoW to complete syllabus,Student Motivation
 
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HOW TO COMPLETE FULL SYLLABUS IN 1 DAY/NIGHT THAT MEANS IN AS LESS TIME AS POSSIBLE PAHLE TOH YE BATAO KI EK RAAT MEIN POORA SYLLABUS KHATAM KARNA HAI ISKA MATLAB PAHLE SE KYA KAR RHE THE ?KHAIR CIVIL BEINGS REGULARLY FOLLOW KARNE WALE JANTE HAIN CONSISTENCY KI IMPORTANCE. ANYWAYS…JO HO GAYA SO HO GAYA … FAIL HO GAYE TOH EK SAAL KHARAB….SO JITNA TIME BACHA HAI USKA FULL USE KARNA SIKHATA HUN MAIN AAP LOGON KO…. KAM TIME BACHA HAI AUR SUBJECT KHATAM KARNA HAI EXAM SE PAHLE…TOH I CAN HELP YOU WITH SOME IMPORTANT TIPS JO AAPKO SURELY HELP KARENGE….STEP BY STEP APPROACH HAI…LOGICAL HAI…UDI UDI BAATEIN NAHI HAIN … SABSE PAHLE TOH BELIEVE RAKHO…PAHLE BHI KAYI BAAR AAPNE ONE NIGHT PAHLE APNA SYLLABUS KHATAM KIYA HAI …. BUT LEARNING AISE NAHI HOTI… AAGE SE PLEASE AISA MAT KARNA….LAST MEIN EK POWER TIP DUNGA…USKO MISS MAT KARNA… BEHERHAAL…1. BELIEF RAKHO … KI AAP KAR SAKTE HO … starting mein aap bahut zyada fresha aur motivated rahoge…do ghante ke baad bura haal ho jata hai…toh belief strong belief rakhna zaruri hai…ki ho jaega…keep calm. 2. REVIEW KAR LO POORA SYLLABUS … AUR MARK KAR LO SABSE IMPORTANT AREAS …MARKS DISTRIBUTION KE HISAAB SE 3. KOSHISH KAREIN KI ATLEAST 70% SYLLABUS COVER HO JAYE. SELECT KAR LEIN VO KAM SE KAM TOPICS AUR CHAPTERS JINSE MILKE 70% QUESTIONS AATE HAIN. YE TOTAL SYLLABUS KA 40-50% HI HOTA HAI… 4. LOOK FOR THE NOTES AND MATERIAL. CHECK KAR LO PAHLE SE …AAPKE PAAS SARA MATERIAL HAI YA NAHI…AGAR NAHI HAI TOH ARRANGE IT NOW… 5. SARA MATERIAL MIL JANE KE BAAD…FIND A QUITE SPOT. …HAR DISTRACTION SE DOOR. …MOBILE…FEK DO…agar ab bhi aap khud ko control nahi kar pa rhe ho…toh fir Bhagwan bhi aapki madad nahi kar sakta…kitna bhi power tip mil jaye…kuch fayda nahi hona…distractions kill focus….SHANT JAGAH LEIN. GHAR WALON KO APNA TIME TABLE BATA DEIN. DOSTON KO PAHLE SE NAA KAH DEIN. POWER TIP … 6. TEXTBOOK MEIN SABSE PAHLE SUMMARIES DEKHEIN…AUR UNN TOPICS KO QUESTIONS KO EK BAAR PADH LEIN … ISSE KYA FAYDA HOGA ? ISSE JAB AAP PADH RHE HONGE USS TOPIC KO DETAIL MEIN TOH AAPKO PAHLE SE IDEA HOGA KI YE TERM, YA FIR ISSE RELATED QUESTION EXAM MEIN AAYA HAI …TOH USPE AAPKA ZYADA DHYAN JAEGA…. ------------------- CIVIL BEINGS CHANNEL IS TO EMPOWER STUDENTS WITH PRACTICAL KNOWLEDGE ABOUT LIFE AND ALSO HELPING UNDERPRIVILEGED STUDENTS IN TERMS OF HEALTHCARE AND EDUCATION. ---------------- JOIN ME PERSONALLY HERE www.facebook.com/civilbeings ------------- Chat with me here Instagram @civilbeings ----------- Support us on Patreon www.patreon.com/civilbeings --------- Subscribe! Share! Support!
Views: 8057749 CIVIL BEINGS
mod07lec34
 
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Conducting one-way ANOVA
Analyzing the Cloudera Hortonworks Merger
 
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Breaking Big Data News last was about the Cloudera Hortonworks merger. What does that mean for the Hadoop Ecosystem? In this episode of the Big Data Beard YouTube show Brett Roberts and Thomas Henson will analyze the merger of the two premier Hadoop Ecosystem distributors. Find out our predictions for the future of Cloudera-Hortonworks and the Hadoop Community as a whole. Be sure to leave comments on your prediction from the Cloudera Hortonworks merger. ► GROW YOUR BIG DATA BEARD - Site devoted to "Exploring all aspects of Big Data & Analytics" ◄ https://bigdatabeard.com/ ► BIG DATA BEARD PODCAST - Subscribe to learn what's going on in the Big Data Community ◄ https://bigdatabeard.com/subscribe-to-podcast/ ► CONNECT ON TWITTER ◄ https://twitter.com/bigdatabeard
Views: 883 Big Data Beard
SCGIS: Whale Watch - Developing Models to Predict Blue Whale Distribution in Near R
 
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Presented by: Helen Bailey (Univeristy of Maryland, Center for Environmental Science) and Briana Abrahms (NOAA's Southwest Fisher Science Center Fellow) Blue whales (Balaenoptera musculus) are listed as Endangered under the U.S. Endangered Species Act due to population depletion from commercial whaling. In the eastern North Pacific, ship strikes remain the largest threat to the recovery of this protected species. Static management approaches along the U.S. West Coast are being implemented to direct traffic into designated shipping lanes, yet whale distributions are dynamic and may shift in response to changing environmental conditions, necessitating integration of dynamic management approaches. We developed a dynamic, near real-time blue whale distribution model with the aim to mitigate ship strike risk in a project called WhaleWatch. This model is now being further refined by examining potential changes in predictive skill by developing distribution models using a) daily surface and subsurface variables from a data-assimilative regional ocean model compared to monthly remotely-sensed environmental data, and b) an ensemble modeling approach with multiple datasets (satellite tags and ship surveys) and methods (Generalized Additive Mixed Models and Boosted Regression Trees) compared to a single-model approach. Dynamic, high-resolution species distribution models with strong predictive performance are a valuable tool for targeting management needs in near real-time. This general approach is readily transferable to other species and spatial management needs.
Views: 63 databasin
Meeting Federal Research Requirements for Data Management Plans, Public Access, and Preservation
 
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With the deadlines for achieving public access to scientific research data in digital formats approaching (October 2015 and January 2016), this webinar recording provides practical advice and resources for writing data management plans as well as tips for evaluating in-house or external public access data sharing services that meet federal research requirements. It begins with a brief update on agency responses to the 2013 OSTP memo, “Increasing Access to the Results of Federally Funded Scientific Research,” with focus on Section 4: “Objectives for Public Access to Scientific Data in Digital Formats.” The update on the responses frame the remainder of the session including: • Developing data management plans • Elements of good metadata and preservation standards • Sharing of restricted-use research data • Data curation training for your staff - training resources for the purposes working knowledge when developing data management plans, reviewing data sharing services for compliance, and interpreting agency guidelines Lastly, this recording will introduce you to a cloud-based research data sharing service known as openICPSR for Institutions and Journals. Developed at ICPSR at the University of Michigan, this data sharing service is designed to meet the needs of universities and departments that desire to comply with federal data sharing requirements but are concerned with the technical and financial costs and risk management associated with managing a publicly-accessible data-sharing service onsite. The session content will be of particular interest to Offices of Research/Sponsored Programs, university libraries, data centers, research scientists, and those who manage staff that will need general working knowledge regarding data management plans, sharing and preserving research data, and generally understanding evolving federal requirements regarding scientific data in digital formats. TO DOWNLOAD WEBINAR SLIDES: http://www.icpsr.umich.edu/files/videos/MeetFederalResearchRequirementsJune2015WebinarICPSR.pptx
Views: 578 ICPSR
The Normal Distribution and the 68-95-99.7 Rule
 
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Thanks to all of you who support me on Patreon. You da real mvps! $1 per month helps!! :) https://www.patreon.com/patrickjmt !! The Normal Distribution and the 68-95-99.7 Rule. In this video, I talk about the normal distribution and what percentage of observed values fall within either 1, 2, or 3 standard deviations from the mean. One specific example is discussed. For more free math video, visit http://PatrickJMT.com
Views: 712674 patrickJMT
VA Logistics Modernization: Examining the RTLS and Catamaran Projects
 
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For more information, visit https://go.usa.gov/xQNBg.
Views: 1492 HouseVetsAffairsGOP
The Definition of the Hazard Function in Survival Analysis
 
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In this video, I define the hazard function of continuous survival data. I break down this definition into its components and explain the intuitive motivation behind each component. Please visit my blog, The Chemical Statistician (http://chemicalstatistician.wordpress.com/), to get your daily lesson on statistics, machine learning or chemistry. On my blog, I write a longer weekly tutorial with deeper explanations and programming examples, and I occasionally write advice columns about working in statistics and science. Please also follow me on Twitter @chemstateric (https://twitter.com/chemstateric)!
Views: 36433 Eric Cai
Spend Analysis Series Episode 4 - Standardizing and Categorizing Data in Spend Analysis Final
 
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In this fourth installment of the Spend Analysis Series, Spend Consultant Jennifer Ulrich explains how to standardize and categorize spend data when examining your company's spend profile.
Digitalization in the Industrial Sector: Implications for Energy, Technology, and Policy
 
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The CSIS Energy & National Security Program and the Technology Policy Program invite you to a discussion with Timothy Lieuwen (Georgia Institute of Technology) and Barbara Humpton (Siemens USA) about the new services and opportunities created for companies and regions as the energy industry continues its trend toward digitalization. The session will begin with a presentation by Dr. Lieuwen, who will explain the findings of Georgia Tech's recent study, Industrial Data in Power Generation. The study is the first phase of an ongoing study of industrial data and regional economic development. Following the presentation, Barbara Humpton will join Dr. Lieuwen to provide perspective on the ecosystem emerging around the digitalization of the energy industry, examining digitalization's potential to simultaneously help increase reliability, decrease cost, and reduce environmental impacts. Speakers will also explain the behavioral standards for those firms handling data from the industrial sector, the role policy plays in the regulation of data transparency/ownership, and which actors have the most influence to establish and define values in this emerging sector. Made possible by general funding to CSIS and the Energy & National Security Program --------------------------------------------------------------------- Subscribe to our channel: http://cs.is/2dCfTve CSIS is the world's #1 defense and national security think tank. Visit http://www.csis.org to find more of our work as we bring bipartisan solutions to the world's greatest challenges. Check out the rest of our videos here: http://cs.is/2dolqpj Follow CSIS on Twitter: http://twitter.com/csis On Facebook: http://www.facebook.com/CSIS.org And on Instagram: http://www.instagram.com/csis/
Time series data in R -  Creating a scatter plot with dates on the x axis - S06
 
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Temporal trends occur in most ecological datasets. Learn R scripts to produce a sequence of dates, and how to create a simple scatter plot showing fish length by date caught. In this session the last R script is revisited to show how statistical data can be exported as a csv file out of R. The script taught will be useful for applications requiring analysis of temporal relationships, and for practicing scripts taught over the last six clips. Download support material; http://oceaniascientificservices.com.au/product/session-06-ss-timeseries/ * * * An Introduction to Data Analysis in R * * * An interactive and informative introduction to R programming for science. R is a free software environment for data management, statistical computing and graphics. In this six part series, watch and follow along as you are introduced to the concepts of data analyses from developing your research question, installing R to creating some simple scripts. Based on extensive experience managing experimental and field data, describing data, running temporal and spatial statistical analyses and mathematical models the experts at Oceania Scientific Services offer their knowledge. These clips are designed to provide a functional introduction for learning R by developing an understanding and appreciation of the thinking that occurs outside of R. By the end of this series you will have a taste of the steps between research, data, visualization and analysis. Dr Amanda Neilen is the principal scientist at Oceania Scientific Services. She lectures in applied mathematics and R at a university in South-East Queensland, Australia, and runs R workshops for businesses and researchers alike. With over 10 year experience with the R scripting language and a passion for answers, she was very excited at the opportunity to be involved with the development and delivery of the online series. Learn more https://oceaniascientificservices.com.au/
SAP HANA Academy - SDA: Connecting with MSSQL (1/2) [SPS 07]
 
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In this video examining new features of SAP HANA SPS 7 release, we will take a look at the Smart Data Access capabilities to connect to a remote MSSQL server. This video is part 1 of 2.
Views: 13371 SAP HANA Academy
Using "big data" for transportation analysis: A case study of the LA Metro Expo Line
 
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The video begins at 2:25. Friday, October 3, 2014 Mohja L. Rhoads, Senior Research Associate, South Bay Cities Council of Governments Friday, October 3, 2014 Access to a comprehensive historical archive of real-time, multi-modal multi-agency transportation system data has provided a unique opportunity to demonstrate how “big data” can be used for policy analysis, and to offer new insights for planning scholarship and practice. We illustrate with a case study of a new rail transit line. We use transit, freeway, and arterial data of high spatial and temporal resolution to examine transportation system performance impacts of the Exposition (Expo) light rail line (Phase 1) in Los Angeles. Using a quasi-experimental research design, we explore whether the Expo Line has had a significant impact on transit ridership, freeway traffic, and arterial traffic within the corridor it serves. Our results suggest a net increase in transit ridership, but few effects on traffic system performance. Given the latent travel demand in this heavily congested corridor, results are consistent with expectations. The benefits of rail transit investments are in increasing transit accessibility and person throughput within high-demand corridors; effects on roadway traffic are small and localized.
Views: 2930 TREC at PSU
Security Policy and Enterprise Key Management To centrally Manage Encryption Keys from Vormetric
 
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This is an excerpt of Vormetric's whitepaper: Simplifying IT Operations Securing and Controlling Access to Data Across the Enterprise. http://www.Vormetric.com/key82 .The whitepaper outlines the challenges of enterprise key management and details ways to minimize the risk. This whitepaper from Vormetric on Key management strategy strives to provide the reader with an understanding, of the importance of encryption key management and of its evolution. Additionally, understanding that companies today require actionable information, the paper provides the reader with a set of criteria for encryption key management as well as an understanding of the challenges that may be faced. This is followed by a review of the recent industry initiatives and compliance regulations that are shaping the future of key management strategy. Lastly, the paper describes Vormetric's Key Management, a component of the Vormetric Data Security product family. According to the whitepaper, encryption key management should meet four primary criteria: 1. Security -- In implementing a comprehensive data security strategy, organizations are well - advised to consider the security of the encryption keys. Where are they stored and how are they protected? Improper key management means weak encryption, and that can translate into vulnerable data. 2. Availability -- In addition to being secure, the keys must ensure that the data is available when it is needed by the system or user. Key management practices that add complexity can decrease availability or add overhead to the network. That results in damage to the over efficiency of the network. 3. Scalability and Flexibility -- Growth and change are inevitable in an organization. The key management solution should be able to address heterogeneous, distributed environments so as not to hamper either growth or change. 4. Governance and Reporting -- Reporting is essential to proper institutional governance. Often, third party entities (be they customers or regulatory authorities) will request, and in some cases mandate, proper governance and reporting of key management. That means implementing and enforcing things like separation of duties, authorization process and key lifecycle management.
Views: 1738 Vormetric
Using data to improve the sustainability of livestock production
 
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The choice to eat animal products is a complex one. While our ancestors depended on animal source foods for vital nutrients, modern diets can provide essential nutrition through plant-based ingredients alone. And yet, globally, average meat consumption per person is higher than ever before. This upsurge has raised serious concerns over the impact of animal- based foods on global sustainability. Now, a special issue of the journal animal has brought together seven articles examining various aspects of livestock production to provide an evidence-driven starting point for sustainable practice. The special issue stems from the 2016 conference on ‘Steps to Sustainable Livestock’, organized by the Global Farm Platform Initiative. The GFP comprises 15 model farms in 11 countries. Although each facility is distinct, they hold a shared mission: to understand the environmental impact of different agricultural practices across varied climates and ecosystems, while also assessing the ability to meet global food requirements. One area of research focuses on the link between livestock and human health. A large proportion of human disease originates from or is otherwise linked to livestock disease. One article proposes a classification system for this relationship that can help prioritize, identify, and deliver appropriate health interventions. Another examines how consumption of meat and milk can help humans maintain a healthy diet at different life-stages. The issue also explores the importance of ruminant animals in turning otherwise indigestible plant material into high-quality food. Three articles explore feeding strategies for ruminants — including the use of insects — to decrease the use of cereal grains as a feed source. The final subject examined is the trade-offs that arise when looking at different ways to minimize the environmental impact of livestock production. One article uses mathematical modeling to explore ways of enhancing phosphorous recycling, while another focuses on the potential of a farm “platform” — an actual farm equipped with high-tech instruments to measure water flow and nutrient distribution — to identify metrics that can serve as surrogates for environmental health. Although seven papers can’t address all the ways to improve the societal and environmental sustainability of livestock production, the collection provides a solid foundation to help guide the continued evolution of best practices that help address societal concerns about livestock production. View the special topic here: https://www.cambridge.org/core/journals/animal/issue/AEB72BDDF9BD83C90714D94AF0A297C2 Editorial: Gill et al. “Livestock production evolving to contribute to sustainable societies.” animal (2018). https://doi.org/10.1017/S1751731118000861 Review: Dairy foods, red meat and processed meat in the diet: implications for health at key life stages I. Given https://doi.org/10.1017/S1751731118000642 Closing the phosphorus cycle in a food system: insights from a modelling exercise R. J. van Kernebeek, S. J. Oosting, M. K. van Ittersum, R. Ripoll-Bosch, I. J. M. de Boer https://doi.org/10.1017/S1751731118001039 Review: Use of human-edible animal feeds by ruminant livestock M. Wilkinson, M. R. F. Lee https://doi.org/10.1017/S175173111700218X Review: Optimizing ruminant conversion of feed protein to human food protein A. Broderick https://doi.org/10.1017/S1751731117002592 Review: Feed demand landscape and implications of food-not feed strategy for food security and climate change P. S. Makkar https://doi.org/10.1017/S175173111700324X Review: Animal health and sustainable global livestock systems D. Perry, T. P. Robinson, D. C. Grace https://doi.org/10.1017/S1751731118000630 Roles of instrumented farm-scale trials in trade-off assessments of pasture-based ruminant production systems Takahashi, P. Harris, M. S. A. Blackwell, L. M. Cardenas, A. L. Collins, J. A. J. Dungait, J. M. B. Hawkins, T. H. Misselbrook, G. A. McAuliffe, J. N. McFadzean, P. J. Murray, R. J. Orr, M. J. Rivero, L. Wu, M. R. F. Lee https://doi.org/10.1017/S1751731118000502 Video produced by https://www.researchsquare.com
Views: 371 Cambridge Core
How to Use the Outliers Function in Excel
 
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See more: http://www.ehow.com/tech/
Views: 68448 eHowTech
Variability of Stock Return Standard Deviation | Corporate Finance | CPA Exam BEC|CMA Exam |Chp12 p3
 
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The variance essentially measures the average squared difference between the actual returns and the average return. The bigger this number is, the more the actual returns tend to differ from the average return. Also, the larger the variance or standard deviation is, the more spread out the returns will be. The way we will calculate the variance and standard deviation will depend on the specific situation. In this chapter, we are looking at historical returns; so the procedure we describe here is the correct one for calculating the historical variance and standard deviation. If we were examining projected future returns, then the procedure would be different. NORMAL DISTRIBUTION For many different random events in nature, a particular frequency distribution, the normal distribution (or bell curve), is useful for describing the probability of ending up in a given range. For example, the idea behind “grading on a curve” comes from the fact that exam score distributions often resemble a bell curve.
Customer-centric hotel experiences - Nick Price keynote at conneXion Munich
 
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Discover the future hotel experience, examining the guest journey, customer loyalty, hotel inventory pricing and distribution, and opportunities for applied business intelligence, highlighting current hospitality industry pain points, and the very real potential for hospitality business improvement introduced by a Retail Unified Commerce Strategy. Find out more about LS Retail software solutions for hotels: https://www.lsretail.com/industries/retail/software-leisure-entertainment-businesses/
Views: 71 LS Retail
Radiolarian Micropalaeontology: Analysing Radiolarian Microfossil Data.
 
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Professor Simon Haslett discusses analysing radiolarian microfossil data. Radiolaria are marine single-celled organisms that possess a silica shell and are preserved in the fossil record. Radiolarian data can be analysed by individual species plots/graphs, or through numerical and statistical analysis of assemblage datasets. Such data can be used in stratigraphy to date layers of rock and sediment through geological time, and also to reconstruct past environments and establish palaeoclimate history. Simon Haslett is Professor of Physical Geography and Director of the Centre for Excellence in Learning and Teaching at the University of Wales, Newport. New videos are regularly added so please subscribe to the channel. Camera operator and editor: Jonathan Wallen.
Views: 557 ProfSimonHaslett
Access Control System
 
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This system provides the improved access security solution based on the cutting edge technology, such as rendering 3D virtual space onto monitors, applying a CCTV images to texture, a image used in virtual space and controlling users' viewpoints, with easy control by the functional buttons on screens while monitoring the server. The system decides the permission of the access and devices at a certain place and at a certain time and also records the entering moment with examining a visitor through the images.
Views: 124 KEUMSUNG
PCI Requirement 3.6.3 Secure Cryptographic Key Storage
 
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If your organization is storing PCI-related data using encryption, those keys must be stored securely, as PCI Requirement 3.6.3 commands, “Secure cryptographic key storage.” If your key storage is securely stored, has the appropriate protections, and access is limited to the fewest number of people and locations as possible, you prevent your organization from being susceptible to an attack. The PCI DSS further explains, “The encryption solution must store keys securely, for example, by encrypting them with a key-encrypting key. Storing keys without proper protection could provide access to attackers, resulting in the decryption and exposure of cardholder data.” You assessor should test your compliance with PCI Requirement 3.6.3 by examining your organization’s key management program and its procedures and methods to verify that they specifically outline and implement that secure storage of keys. If you store, process, or transmit cardholder data, interact with payment card data in any way, or have the ability to impact someone else’s cardholder information or the security of that information, you are subject to comply with the PCI DSS. This exclusive video series, PCI Demystified, was developed to assist your organization in understanding what the Payment Card Industry Data Security Standard (PCI DSS) is, who it applies to, what the specific requirements are, and what your organizations needs to know and do to become compliant. Learn more at https://kirkpatrickprice.com/video/pci-requirement-3-6-3-secure-cryptographic-key-storage/ Video Transcription Once again, if you’re encrypting information, whether this be PII, PHI, PCI-related data, if you have implemented encryption as a part of this methodology, we want to make sure that those keys you’re using are stored securely. We want to make sure that access has been limited to the fewest possible number of individuals. You need to have protections around them so that in the event that somebody should compromise the server, they don’t gain access to the encryption keys or the decryption keys themselves. So, your assessor is going to be working with you and asking how you’ve gone about doing that. They’re going to be looking at your documented procedures for secure key distribution and secure key storage and how that rolls out. If you have an HSM in a FIPS-compliant device, the controls that are there are pretty much established by the technology. In short, once again, where you are storing these keys, they need to be stored securely. Stay Connected Twitter: https://twitter.com/KPAudit LinkedIn: https://www.linkedin.com/company/kirkpatrickprice-llc Facebook: https://www.facebook.com/kirkpatrickprice/ More Free Resources PCI Demystified: https://kirkpatrickprice.com/pci-demystified/ Blog: https://kirkpatrickprice.com/blog/ Webinars: https://kirkpatrickprice.com/webinars/ Videos: https://kirkpatrickprice.com/video/ White Papers: https://kirkpatrickprice.com/white-papers/ About Us KirkpatrickPrice is a licensed CPA firm, PCI QSA, and a HITRUST CSF Assessor, registered with the PCAOB, providing assurance services to over 600 clients in more than 48 states, Canada, Asia, and Europe. The firm has over 12 years of experience in information security and compliance assurance by performing assessments, audits, and tests that strengthen information security and internal controls. KirkpatrickPrice most commonly provides advice on SOC 1, SOC 2, HIPAA, HITRUST CSF, PCI DSS, ISO 27001, FISMA, and CFPB frameworks. For more about KirkpatrickPrice: https://kirkpatrickprice.com/ Contact us today: 800-770-2701 https://kirkpatrickprice.com/contact/
Views: 423 KirkpatrickPrice
Evo Pricing: What we do and how we do it
 
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http://www.evopricing.com Last week we asked the data scientists in our Turin office to explain, in their own words, what Evo Pricing does and the "secret sauce" we use to get great results for our clients. TRANSCRIPT: [Intro Music] Fabrizio Fantini (Founder of Evo Pricing): Evo Pricing is based on my PhD research work that I was doing while I was in Boston, at Harvard University. The company essentially takes data from customers, takes data from the market and estimates the probability of sales, and figures out what are the right promotions, product prices and the optimal product assortment. Elena (Data Scientist): Based on sales of the last week I can recommend which stores need specific items, which ones can exchange their items. I give a specific suggestion, for example: Store A has to send these 3 items to Store B, rather than put them in stock. Fabrizio Fantini: Our solutions cover a wide spectrum of decisions: planning, strategy, bid structure, the placing of articles in the stores, discounts, price optimization, sale management, targeted promotions - for example in the insurance sector in order to retain customers. Viola (Data Scientist): We help customers to improve their market prices by examining, for example, which competitors are moving. We study their story in a certain way, what they have in stock, the performance of past sales. Fabrizio Fantini: We often liken ourselves to satellite navigators. Why? First of all, because of our working method. A sat-nav has some complicated logic inside but then the interface with the user is very simple: it tells you if you have to go straight, left or right; it's a bit like what we are doing. We use a lot of data and algorithms that are quite complex to then give fairly simple indications to the management. Giuseppe (Senior Data Scientist): Companies have a lot of data but sometimes they do not find the right way to look at them. We try to help them to interpret what's going on. Our recommendation comes from a deep understanding of the phenomenon. Fabrizio Fantini: The amount of data available to people and companies is exploding and it’s exploding specifically because the cost is decreasing exponentially. But all of these data are like a noise and so in reality the difficulty of our job is increasing, not diminishing. Giuseppe: Since reality is complex and data is complex, fragmented, we need to use tools to capture data fragmentation and their complexity, tools that go beyond classical enterprise productivity analysis done by using Excel. Blanca (Data Scientist): We're studying what the results are, what's going on... you can see if things are getting better or getting worse. When they're going well you try to make them go even better while, when they're going worse, you say, "OK, maybe I would change some things here, maybe this item is too expensive and I would do it cheaper, or maybe it's too cheap". Elena: And then there's also the direct intervention of the managers in the stores, so every week the shopkeeper can give us their opinion on what they think will be selling or not selling in the next few weeks. Amedeo (Data Scientist): The strategy must always adapt to the needs of the individual case, of the client. Viola: We have to understand well what our customer expectations are. Amedeo: We start with an idea that can be a good approximation of the reality but, moving forward, we can find what might be the problems, things to improve or to change. Fabrizio Fantini: Just like a car driver that changes the route and then the navigator updates the entire route, so we learn from decisions that management takes and we try to adapt all this automatically, improving the quality of our recommendations. Elena: We work on all these things together, to merge the machine prediction with the human factor. Fabrizio Fantini: Our first fashion client in Italy, Miroglio Group, has publicly talked about one of our most successful and scientifically interesting experiences. We did a research project with them on distribution of items in retail fashion stores. We demonstrated that the involvement of people working in the store helps artificial intelligence to improve the quality of solutions. Algorithms improve predictions but do not win alone. We believe in what we call a new alliance between man and machine. Elena: It's a collaboration between the two things. Fabrizio Fantini: The quality of human intuition doubles the effectiveness of solutions, so it is a very significant improvement. Elena: We've seen that this alliance between man and machine brings good results. [Outro music]
Views: 626 Evo Pricing
Busting Myths About China’s Overseas Development Program With New Data with Dr. Brad Parks
 
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Over the last decade, China has emerged as one of the largest suppliers of international development finance, with a large and growing overseas development budget. Consequently, no other non-Western country has drawn as much scrutiny for its development activities. Yet China does not release detailed information about the “where, what, how, and to whom” of its development aid. This presents an obstacle for policy makers, practitioners, and analysts who seek to understand the distribution and impact of Chinese development finance. Since 2013, AidData has led an ambitious effort to correct this problem by developing an open source data collection methodology called Tracking Underreported Financial Flows (TUFF) and maintaining a publicly available database of Chinese development projects around the world. AidData has also teamed up with a group of economists and political scientists from leading universities around the world to conduct cutting-edge research with this database, examining differences and similarities in the levels, priorities, and consequences of Chinese and American development finance. On March 13, Dr. Brad Parks, executive director of AidData and a faculty member at the College of William and Mary, will discuss the organization’s work with the National Committee in New York City. Drawing on advanced techniques that include using nighttime light and deforestation data from high-resolution, satellite imagery, Dr. Parks will present new findings on the intended economic development impacts and the unintended environmental impacts of Chinese development projects. Bio: Brad Parks is AidData’s executive director and a research faculty member at the College of William and Mary’s Institute for the Theory and Practice of International Relations. His research focuses on the cross-national and sub-national distribution and impact of international development finance, and the design and implementation of policy and institutional reforms in low-income and middle-income countries. His publications include Greening Aid?, Understanding the Environmental Impact of Development Assistance (Oxford University Press, 2008) and A Climate of Injustice: Global Inequality, North-South Politics, and Climate Policy (MIT Press, 2006). He is currently involved in several empirical studies of the upstream motivations for, and downstream effects of, Chinese development finance. His research in this area has been published in the Journal of Conflict Resolution, the Journal of Development Studies, China Economic Quarterly, and the National Interest. From 2005 to 2010, Dr. Parks was part of the initial team that set up the U.S. Government's Millennium Challenge Corporation (MCC). As acting director of Threshold Programs at the MCC, he oversaw the implementation of a $35 million anti-corruption and judicial reform project in Indonesia and a $21 million customs and tax reform project in the Philippines. Dr. Parks holds a Ph.D. in international relations and an M.Sc. in development management from the London School of Economics and Political Science.
Examining Travel & Entertainment Expenses
 
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If you are reviewing entertainment expenses and find discrepancies, how often do you hear management say, “What’s the big deal? How bad could it be?” Learn why internal controls over T&E expenditures are a critical component of the control environment. Topic: Auditing and examining Travel and Entertainment Expenses: Expense Reimbursement Fraud Speaker: Lynn Fountain Access complete course at https://goo.gl/jTg1rp. Please visit https://www.compliance.world for more BFSI videos.
Views: 68 Compliance World
Cloudera surges on merger with software rival Hortonworks
 
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CNBC's Seema Mody reports on Cloudera stock jumping after it announced an all-stock merger of equals with competitor Hortonworks.
Views: 1085 CNBC Television
MATLAB GEV
 
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Modelling Data with the Generalized Extreme Value Distribution This Modelling Data with the Generalized Extreme Value Distribution shows how to fit the generalized extreme value distribution using maximum likelihood estimation. The extreme value distribution is used to model the largest or smallest value from a group or block of data.
Extreme value theory for heatwave risk assessment
 
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RSS Annual Conference. 7 – 10 September 2015, Exeter University Jonathan Tawn Lancaster University, Professor of Statistics
Views: 1553 RoyalStatSoc
What's New In Oracle Manufacturing Analytics? [Examining Oracle BI Applications 11g: The Series]
 
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http://www.kpipartners.com/watch-whats-new-in-oracle-manufacturing-analytics ... KPI endorses the Oracle Manufacturing Analytics solution as one that provides end-to-end visibility into manufacturing operations by integrating data from across the enterprise value chain. The Oracle offering enables organizations to reduce production costs, improve product quality, minimize inventory levels and respond faster to customer demands. Manufacturing Analytics, as part of the latest release of the BI Applications (11.1.1.7.1), can provide support for Discrete Manufacturing analysis and produce pegging reports to show the relationship between demand and supply. Watch this 'Examining Oracle BI Applications 11g: The Series' session that takes a deep dive into the latest version of this Oracle BI Applications solution and how this can extend and organization's business intelligence footprint to support the Manufacturing modules in Oracle E-Business Suite. Manufacturing Analytics can also provide tremendous analytical value to organizations who wish to: gain visibility into manufacturing schedules gain visibility into cost gain visibility into quality and service levels correlate work order information with production plans reduce work order cycle time and aging of open work orders perform non-conformance and disposition analysis improve insight into raw materials and finished goods. Areas of examination for this session include: Common Business Questions for Manufacturing Departments Overview of Oracle Manufacturing Analytics The Manufacturing Executive Dashboard The Production Performance Dashboard The Inventory Dashboard The Production Cost Dashboard The Plan-To-Produce Dashboard Performance Summary By Plant Reporting Supply and Demand Analysis Reports Resource Utilization Reporting Work Order Details Reporting Inventory Snapshot Reporting Inventory Aging Reports Production Costs By Top 10 General Ledger Accounts Cost Distribution Trend Reporting Plan-To-Produce Linearity Report Plan Comparison Report
Views: 798 kpipartners
Stata Video 4 - Recoding Existing Variables and Frequency Tables
 
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Besides generating new variables, we often need to change current values/coding schemes of existing variables. In this video, we show you how to do so via "recode" and "replace" commands in Stata. Also, you will see how to list frequency tables in Stata.
Views: 1647 Lei Zhang
How Enhanced IT/OT Integration can Help Enable the Future Distribution Network
 
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Driving effective IT/OT integration will be critical for utilities, enabling data and operations to seamless work together to achieve business outcomes and greater future performance. Learn more: http://bit.ly/2jcfmmn
Views: 1514 Accenture
Tech Trends for Highly Effective Colocation Deployments
 
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In this webinar, we’ll discuss how you can ensure the most from your deployment, from innovative thinking on remote monitoring to capacity planning and more. This session is moderated by 451 Research’s Andrew Donoghue, Raritan's Jon Inaba and Equinix’s Steve Abraham. They will discuss how smart data center managers can reduce costs, lower risks, and get the most out of their colocation contract and provider. About the Speakers: ANDREW DONOGHUE Andrew Donoghue is the European Research Manager at 451 Research, and is a member of 451 Research’s Datacenter Technologies and Eco-Efficient IT practices. He is the author of several major reports covering eco-efficient IT; power management; policy, legislation and compliance; and datacenter management and energy-efficiency. He has represented 451 Research at the Green Grid and other major datacenter events. STEVE ABRAHAM Steven Abraham is Senior Manager of Equinix Infrastructure Services (EIS) in Ashburn, VA. As one of the co-creators of the EIS business line, Steve has grown the business by focusing on meeting customer data center requirements, including physical security and power usage. JON INABA Jon Inaba joined Raritan when the company entered the nascent intelligent power management market. Jon’s passion for helping customers design and implement power management solutions to create energy efficient and intelligent data centers has helped Raritan become the leader in intelligent power. To learn more visit: http://www.raritan.com/
Views: 365 Raritan
Market Research Analysts CareerSearch.com
 
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Career Search Market and survey researchers gather information about what people think. Market, or marketing, research analysts help companies understand what types of products people want and at what price. They also help companies market their products to the people most likely to buy them. Gathering statistical data on competitors and examining prices, sales, and methods of marketing and distribution, they analyze data on past sales to predict future sales. Market research analysts devise methods and procedures for obtaining the data they need. Market and survey researchers generally have structured work schedules. They often work alone, writing reports, preparing statistical charts, and using computers, but they also may be an integral part of a research team. Market researchers who conduct personal interviews have frequent contact with the public. Most work under pressure of deadlines and tight schedules, which may require overtime. Travel may be necessary. Median annual earnings of market research analysts in May 2006 were $58,820. CareerSearch.com
Views: 127 careersearchcom