Meet a data scientist who is using big data to create the medical systems of the future. Dr. Eric Schadt of the Icahn Institute is creating algorithms that can detect ailments and chart personalized health profiles. Subscribe to HuffPost today: http://goo.gl/xW6HG Get More HuffPost Read: http://www.huffingtonpost.com/ Like: https://www.facebook.com/HuffingtonPost Follow: https://twitter.com/HuffingtonPost
Views: 34872 HuffPost
Here we give you a set of numbers and then ask you to find the mean, median, and mode. It's your first opportunity to practice with us! Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/probability/descriptive-statistics/central_tendency/e/mean_median_and_mode?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Watch the next lesson: https://www.khanacademy.org/math/probability/descriptive-statistics/central_tendency/v/exploring-mean-and-median-module?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Missed the previous lesson? https://www.khanacademy.org/math/probability/descriptive-statistics/central_tendency/v/statistics-intro-mean-median-and-mode?utm_source=YT&utm_medium=Desc&utm_campaign=ProbabilityandStatistics Probability and statistics on Khan Academy: We dare you to go through a day in which you never consider or use probability. Did you check the weather forecast? Busted! Did you decide to go through the drive through lane vs walk in? Busted again! We are constantly creating hypotheses, making predictions, testing, and analyzing. Our lives are full of probabilities! Statistics is related to probability because much of the data we use when determining probable outcomes comes from our understanding of statistics. In these tutorials, we will cover a range of topics, some which include: independent events, dependent probability, combinatorics, hypothesis testing, descriptive statistics, random variables, probability distributions, regression, and inferential statistics. So buckle up and hop on for a wild ride. We bet you're going to be challenged AND love it! About Khan Academy: Khan Academy is a nonprofit with a mission to provide a free, world-class education for anyone, anywhere. We believe learners of all ages should have unlimited access to free educational content they can master at their own pace. We use intelligent software, deep data analytics and intuitive user interfaces to help students and teachers around the world. Our resources cover preschool through early college education, including math, biology, chemistry, physics, economics, finance, history, grammar and more. We offer free personalized SAT test prep in partnership with the test developer, the College Board. Khan Academy has been translated into dozens of languages, and 100 million people use our platform worldwide every year. For more information, visit www.khanacademy.org, join us on Facebook or follow us on Twitter at @khanacademy. And remember, you can learn anything. For free. For everyone. Forever. #YouCanLearnAnything Subscribe to KhanAcademy’s Probability and Statistics channel: https://www.youtube.com/channel/UCRXuOXLW3LcQLWvxbZiIZ0w?sub_confirmation=1 Subscribe to KhanAcademy: https://www.youtube.com/subscription_center?add_user=khanacademy
Views: 2054737 Khan Academy
The Minimum Data Set is part of the U.S. federally mandated process for clinical assessment of all residents in Medicare or Medicaid certified nursing homes. This process provides a comprehensive assessment of each resident's functional capabilities and helps nursing home staff identify health problems. Resource Utilization Groups are part of this process, and provide the foundation upon which a resident's individual care plan is formulated. MDS assessment forms are completed for all residents in certified nursing homes, regardless of source of payment for the individual resident. MDS assessments are required for residents on admission to the nursing facility and then periodically, within specific guidelines and time frames. In most cases, participants in the assessment process are licensed health care professionals, usually Registered Nurses, employed by the nursing home. MDS information is transmitted electronically by nursing homes to the MDS database in their respective states. MDS information from the state databases is captured into the national MDS database at Centers for Medicare and Medicaid Services. This video is targeted to blind users. Attribution: Article text available under CC-BY-SA Creative Commons image source in video
Views: 3131 Audiopedia
Learn the difference between Nominal, ordinal, interval and ratio data. http://youstudynursing.com/ Research eBook on Amazon: http://amzn.to/1hB2eBd Check out the links below and SUBSCRIBE for more youtube.com/user/NurseKillam For help with Research - Get my eBook "Research terminology simplified: Paradigms, axiology, ontology, epistemology and methodology" here: http://www.amazon.com/dp/B00GLH8R9C Related Videos: http://www.youtube.com/playlist?list=PLs4oKIDq23AdTCF0xKCiARJaBaSrwP5P2 Connect with me on Facebook Page: https://www.facebook.com/NursesDeservePraise Twitter: @NurseKillam https://twitter.com/NurseKillam Facebook: https://www.facebook.com/laura.killam LinkedIn: http://ca.linkedin.com/in/laurakillam Quantitative researchers measure variables to answer their research question. The level of measurement that is used to measure a variable has a significant impact on the type of tests researchers can do with their data and therefore the conclusions they can come to. The higher the level of measurement the more statistical tests that can be run with the data. That is why it is best to use the highest level of measurement possible when collecting information. In this video nominal, ordinal, interval and ratio levels of data will be described in order from the lowest level to the highest level of measurement. By the end of this video you should be able to identify the level of measurement being used in a study. You will also be familiar with types of tests that can be done with each level. To remember these levels of measurement in order use the acronym NOIR or noir. The nominal level of measurement is the lowest level. Variables in a study are placed into mutually exclusive categories. Each category has a criteria that a variable either has or does not have. There is no natural order to these categories. The categories may be assigned numbers but the numbers have no meaning because they are simply labels. For example, if we categorize people by hair color people with brown hair do not have more or less of this characteristic than those with blonde hair. Nominal sounds like name so it is easy to remember that at a nominal level you are simply naming categories. Sometimes researchers refer to nominal data as categorical or qualitative because it is not numerical. Ordinal data is also considered categorical. The difference between nominal and ordinal data is that the categories have a natural order to them. You can remember that because ordinal sounds like order. While there is an order, it is also unknown how much distance is between each category. Values in an ordinal scale simply express an order. All nominal level tests can be run on ordinal data. Since there is an order to the categories the numbers assigned to each category can be compared in limited ways beyond nominal level tests. It is possible to say that members of one category have more of something than the members of a lower ranked category. However, you do not know how much more of that thing they have because the difference cannot be measured. To determine central tendency the categories can be placed in order and a median can now be calculated in addition to the mode. Since the distance between each category cannot be measured the types of statistical tests that can be used on this data are still quite limited. For example, the mean or average of ordinal data cannot be calculated because the difference between values on the scale is not known. Interval level data is ordered like ordinal data but the intervals between each value are known and equal. The zero point is arbitrary. Zero simply represents an additional point of measurement. For example, tests in school are interval level measurements of student knowledge. If you scored a zero on a math test it does not mean you have no knowledge. Yet, the difference between a 79 and 80 on the test is measurable and equal to the difference between an 80 and an 81. If you know that the word interval means space in between it makes remembering what makes this level of measurement different easy. Ratio measurement is the highest level possible for data. Like interval data, Ratio data is ordered, with known and measurable intervals between each value. What differentiates it from interval level data is that the zero is absolute. The zero occurs naturally and signifies the absence of the characteristic being measured. Remember that Ratio ends in an o therefore there is a zero. Typically this level of measurement is only possible with physical measurements like height, weight and length. Any statistical tests can be used with ratio level data as long as it fits with the study question and design.
Views: 334491 NurseKillam
Mean median mode and range statistics Statistics - Mean, Median, Mode how to make paper bag from newspaper https://youtu.be/JoTqwqjdjPs Statistics for Ungrouped Data- How to find Mean Median Mode Finding mean, median, and mode CALCULATE MEAN MEDIAN AND MODE FOR GROUPED DATA Mean; Median; Mode; Standard Deviation Statistics intro: Mean, median, and mode | Data and statistics Central Tendency - Mean Median Mode Range Mean, Median, and Mode - CBSE NCERT Class 9, chapter 14, statistics. class 8, class 7, class 6, class 10. Mode, Mean, and Median - VERY EASY way to learn, Statistics intro: Mean, median, and mode | Data and statistics | 6th grade Introduction to descriptive statistics and central tendency. Ways to measure the average of a set: median, mean, mode. Mean, Median, Mode, and Range Made Easy! Different types of quadrilaterals and their properties class 9 cbse https://www.youtube.com/watch?v=xahcJZu1u9c If you like our videos, subscribe to our channel https://www.youtube.com/channel/UCEVG-1G2sP_CCvRUp3i_fyg Feel free to connect with us at https://www.facebook.com/galaxycoachingclasses/?ref=bookmarks or https://www.facebook.com/galaxymathstricks/ Please Like Our Facebook Page. https://www.facebook.com/galaxycoachingclasses/ Please Follow Me On Instagram https://www.instagram.com/chetanptl12/ Please Follow me on Twitter. https://twitter.com/chetan21385 Have fun, while you learn. Thanks for watching
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Get access to practice questions, written summaries, and homework help on our website! http://wwww.simplelearningpro.com Follow us on Instagram http://www.instagram.com/simplelearningpro Like us on Facebook http://www.facebook.com/simplelearningpro Follow us on Twitter http://www.twitter.com/simplelearningp If you found this video helpful, please subscribe, share it with your friends and give this video a thumbs up!
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An explanation of how to compute the chi-squared statistic for independent measures of nominal data. For an explanation of significance testing in general, see http://evc-cit.info/psych018/hyptest/index.html There is also a chi-squared calculator at http://evc-cit.info/psych018/chisquared/index.html
Views: 951943 J David Eisenberg
Mohsen Bayati of Stanford University explains how machine learning could and is being examined and used to determine ways to make health care more cost-effective. One example is patient readmission rates, with the most common occurrences in from past studies being from elderly and Medicare patients. A variety of reasons persist, but the surprising fact is many of these readmissions could have been avoided with a small amount of preventive care in the first place. Medication mismanagement is among the top reasons, and heart failure also is listed. A patientΓÇÖs lack of access to care outside of the hospital is also a major factor for readmissions.
Views: 988 Microsoft Research
Dr. Manishika Jain in this lecture explains the meaning of Sampling & Types of Sampling Research Methodology Population & Sample Systematic Sampling Cluster Sampling Non Probability Sampling Convenience Sampling Purposeful Sampling Extreme, Typical, Critical, or Deviant Case: Rare Intensity: Depicts interest strongly Maximum Variation: range of nationality, profession Homogeneous: similar sampling groups Stratified Purposeful: Across subcategories Mixed: Multistage which combines different sampling Sampling Politically Important Cases Purposeful Sampling Purposeful Random: If sample is larger than what can be handled & help to reduce sample size Opportunistic Sampling: Take advantage of new opportunity Confirming (support) and Disconfirming (against) Cases Theory Based or Operational Construct: interaction b/w human & environment Criterion: All above 6 feet tall Purposive: subset of large population – high level business Snowball Sample (Chain-Referral): picks sample analogous to accumulating snow Advantages of Sampling Increases validity of research Ability to generalize results to larger population Cuts the cost of data collection Allows speedy work with less effort Better organization Greater brevity Allows comprehensive and accurate data collection Reduces non sampling error. Sampling error is however added. Population & Sample @2:25 Sampling @6:30 Systematic Sampling @9:25 Cluster Sampling @ 11:22 Non Probability Sampling @13:10 Convenience Sampling @15:02 Purposeful Sampling @16:16 Advantages of Sampling @22:34 #Politically #Purposeful #Methodology #Systematic #Convenience #Probability #Cluster #Population #Research #Manishika #Examrace For IAS Psychology postal Course refer - http://www.examrace.com/IAS/IAS-FlexiPrep-Program/Postal-Courses/Examrace-IAS-Psychology-Series.htm For NET Paper 1 postal course visit - https://www.examrace.com/CBSE-UGC-NET/CBSE-UGC-NET-FlexiPrep-Program/Postal-Courses/Examrace-CBSE-UGC-NET-Paper-I-Series.htm types of sampling types of sampling pdf probability sampling types of sampling in hindi random sampling cluster sampling non probability sampling systematic sampling
Views: 351792 Examrace
This video describes five common methods of sampling in data collection. Each has a helpful diagrammatic representation. You might like to read my blog: https://creativemaths.net/blog/
Views: 755810 Dr Nic's Maths and Stats
This is a fantastic intro to the basics of statistics. Our focus here is to help you understand the core concepts of arithmetic mean, median, and mode. Practice this lesson yourself on KhanAcademy.org right now: https://www.khanacademy.org/math/cc-sixth-grade-math/cc-6th-data-statistics/mean-and-median/e/calculating-the-mean?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/mean-and-median/v/mean-median-and-mode?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/histograms/v/interpreting-histograms?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 is a nonprofit with a mission to provide a free, world-class education for anyone, anywhere. We believe learners of all ages should have unlimited access to free educational content they can master at their own pace. We use intelligent software, deep data analytics and intuitive user interfaces to help students and teachers around the world. Our resources cover preschool through early college education, including math, biology, chemistry, physics, economics, finance, history, grammar and more. We offer free personalized SAT test prep in partnership with the test developer, the College Board. Khan Academy has been translated into dozens of languages, and 100 million people use our platform worldwide every year. For more information, visit www.khanacademy.org, join us on Facebook or follow us on Twitter at @khanacademy. And remember, you can learn anything. For free. For everyone. Forever. #YouCanLearnAnything Subscribe to Khan AcademyÂÃÂªs 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: 1902144 Khan Academy
Here are some additional techniques for data mining: 1. Decision Tree Analysis: https://www.youtube.com/watch?v=bJC5S_ViRCo 2. Text mining in Twitter: https://www.youtube.com/watch?v=I0VCGCnquTQ
Views: 116 The Data Science Show
Clicked here http://www.MBAbullshit.com/ and OMG wow! I'm SHOCKED how easy.. No wonder others goin crazy sharing this??? Share it with your other friends too! Fun MBAbullshit.com is filled with easy quick video tutorial reviews on topics for MBA, BBA, and business college students on lots of topics from Finance or Financial Management, Quantitative Analysis, Managerial Economics, Strategic Management, Accounting, and many others. Cut through the bullshit to understand MBA!(Coming soon!) http://www.youtube.com/watch?v=a5yWr1hr6QY
Views: 551567 MBAbullshitDotCom
...with Nursing Professor Lori Cerone. Capital Community College, Hartford, CT
Views: 66413 SeeItNow @ CCC
http://ibm.co/healthcareanalytics Healthcare organizations are leveraging the IBM Big Data & Analytics platform to capture all of the information about a patient to get a more complete view for insight into care coordination and outcomes-based reimbursement models, population health management, and patient engagement and outreach. Successfully harnessing big data unleashes the potential to achieve the three critical objectives for healthcare transformation: Build sustainable healthcare systems Collaborate to improve care and outcomes Increase access to healthcare
Views: 64584 IBM Analytics
The main types of probability sampling methods are simple random sampling, stratified sampling, cluster sampling, multistage sampling, and systematic random sampling. The key benefit of probability sampling methods is that they guarantee that the sample chosen is representative of the population
Views: 136554 Manager Sahab
Examples showing how to apply various tools to perform a Root Cause Analysis. You can get products to help yourself with similar root cause analysis problems at http://bit.ly/2jyMt3C. ----- Links: PMG Results Website: https://www.pmgresults.com/ Have a Question? https://www.pmgresutls.com/contact/ QuikSigma Software Perpetual Licencse: http://bit.ly/2mxagk2 Basic Green Belt Certification: http://bit.ly/2mx5Ycw Advanced Green Belt Certification: http://bit.ly/2nhg8Os Black Belt Certification: http://bit.ly/2mV6Z0z ----- Basic Principles of Root Cause Analysis 00:13 Five whys 00:51 Variation Breakdown/Thought Map 1:52 Pareto Charts 4:02 Process Map, Cause and Effect Matrix, FMEA 4:25 Process Behavior Charts (Control Charts, I-MR Charts) 5:25 Data Mining, Exploratory Data Analysis (EDA) 6:40
Views: 121733 QuikSigma
http://youstudynursing.com/ Research eBook on Amazon: http://amzn.to/1hB2eBd Check out the links below and SUBSCRIBE for more youtube.com/user/NurseKillam For help with Research - Get my eBook "Research terminology simplified: Paradigms, axiology, ontology, epistemology and methodology" here: http://www.amazon.com/dp/B00GLH8R9C Related Videos: http://www.youtube.com/playlist?list=PLs4oKIDq23AdTCF0xKCiARJaBaSrwP5P2 Connect with me on Facebook Page: https://www.facebook.com/NursesDeservePraise Twitter: @NurseKillam https://twitter.com/NurseKillam Facebook: https://www.facebook.com/laura.killam LinkedIn: http://ca.linkedin.com/in/laurakillam Measures of central tendency include descriptive statistics including the mean, median and mode that are used to describe what the average person or response in a particular study is like. It is important as a research consumer to understand how these statistics are calculated and used to summarize and organize information in a study. Before talking about these measures of central tendency, it is important to know what a normal distribution is. The best measure of central tendency depends on a number of things including weather data has a normal distribution or not. The theoretical concept of a normal distribution is covered in more depth in another video, but simply put it is the idea that when data are gathered from interval or ratio level measures and plotted on a graph it will resemble a normal curve. The three measures of central tendency described in this video would all fall at the same midline point on a normal distribution curve. However, if data are not normally distributed certain measures may be better than others. The appropriateness of each measure is also influenced by the level of measurement used in the study. Throughout this video I will have examples of how to calculate the mean, median and mode on the screen. These examples will use the data I made up for a fake study about hours students spend watching online videos and reading for studying purposes. In statistics, mean is synonymous with the average. Whether it is true or not you could try remembering that the average girl can be mean when they want to be. Or, if you can remember what the other two are so you can figure this one out through the process of elimination. You may remember how to calculate averages from math class. To calculate the mean or average of a group of numbers, first add all the numbers. Then, divide by the number of values. The mean or average is the most common, best known and most widely used measure to describe the center of a frequency distribution. The mean is influenced by all data in a Study. For this reason, it works best for symmetrical distributions of data where there are no outliers or extremes. However, the larger the data set the smaller the influence of any extreme scores will be. The mean is the most commonly use measure because it is considered the most reliable measure of central tendency when making inferences from a sample population. However, it is only appropriate for interval and ratio level data. The Median is the value in the middle of a set of data. One way to remember that median means middle is to try associating it with the word medium. Median and medium sound sort of similar. They also both start with the letters MED. A medium pizza or a medium coffee is typically the size in the middle range at a store. If there is an even number of values simply divide the two numbers in the middle by 2. Unlike the Mean, the mode is not influenced by extreme values in a data set. Therefore, it is a good measure to use when distributions are not symmetrical. If a researcher is working with data that are not normally distributed and wants to know what the typical score is the median is likely the best measure to use. In this situation both the mean and median would likely be reported. The median is limited because it is not algebraically defined. Instead it is simply the point in the middle of the data set. While it is useful for ordinal, interval and ratio levels of measurement it cannot be used for nominal data. The Mode is the most frequent value, number or category in a set of data. One way to remember this definition is that Mode sounds like Most. Both mode and most start with the letters MO. The mode is the only measure of central tendency you can use for nominal data. While it can be used for all levels of measurement, it is considered unstable since fluctuations are likely between sample populations. Sometimes there is no mode. If all scores are different the mode does not exist. Sometimes there are multiple modes. If several values occur with equal frequency there are several modes. Unfortunately the mode can't be used for any further calculations in the study -- it can only help to describe the central tendency of the population.
Views: 134450 NurseKillam
Collection of Data (आकड़ों का संकलन) Data are collected by individual research workers or by organization through sample surveys or experiments, keeping in view the objectives of the study. The data collected may be: 1) Primary Data 2) Secondary Data 1) Primary data Primary data means the raw data which has just been collected from the source and has not gone any kind of statistical treatment like sorting and tabulation. 2) Secondary Data Data which has already been collected by someone, may be sorted, tabulated and has undergone a statistical treatment. It is fabricated or tailored data. To View Full Video Lectures Visit - https://bit.ly/2PEEnUC ★ ACCOUNTS VIDEOS ★ https://www.youtube.com/channel/UCAXbiqmSkp9Sse4guGRMqDw?view_as=subscriber ★ COST ACCOUNTING VIDEOS ★ https://www.youtube.com/channel/UCAXbiqmSkp9Sse4guGRMqDw?view_as=subscriber ★ FINANCIAL MANAGEMENT VIDEOS ★ https://www.youtube.com/channel/UCAXbiqmSkp9Sse4guGRMqDw?view_as=subscriber ★ ECONOMICS VIDEOS ★ https://www.youtube.com/channel/UCK5RB8xNW_iOXz-rcGJZyTw?view_as=subscriber ★ INCOME TAX VIDEOS ★ https://www.youtube.com/channel/UCRRFVa1axTUdwZzc4Ta42XQ?view_as=subscriber ★ MATHS VIDEOS ★ https://www.youtube.com/channel/UCaIY3jMl7QDUWN6P6kSUYWw?view_as=subscriber STUDY TIPS ऐसे पढोगे तो हमेशा TOPPER बनोगे | Study Tips https://bit.ly/2QUXaew ENGLISH – Fatafat (Easy Way to Learn English) अंग्रेजी सीखें - फटाफट https://bit.ly/2PoAF4H ★ ExpertMotivation Channel https://bit.ly/2EsPBKC ★ For Any Information Video classes & Face To Face Batches Call +91 9268373738 E-mail: [email protected] (We Prefer emails rather than calls) Call timings Monday to Friday - Morning 10 to Evening 7 FACEBOOK: https://www.facebook.com/VijayAdarshIndia WEBSITE: http://www.vijayadarsh.com
Views: 110523 StayLearning
Thanks to all of you who support me on Patreon. You da real mvps! $1 per month helps!! :) https://www.patreon.com/patrickjmt !! Bayes' Theorem and Cancer Screening. A very real life example of Bayes' Theorem in action. ** According to some data I found online (not sure how accurate it is), mammograms are actually less reliable than the numbers I used! Pretty amazing to me... *
Views: 207941 patrickJMT
Learn how to perform a Chi Square Test with this easy to follow statistics video. I also provided the links for my other statistics videos as well. Chi Square Test - "rolling dice" example https://www.youtube.com/watch?v=1Ldl5Zfcm1Y Hypothesis testing - two tailed test https://www.youtube.com/watch?v=0XXT3bIY_pw Hypothesis testing - one tailed test https://www.youtube.com/watch?v=lNoxKsuJ6Xc Confidence Intervals - with 't' value https://www.youtube.com/watch?v=UmAJJtEo6cQ Practice Quiz - z-test and t-test https://www.youtube.com/watch?v=o_QGaqYAqjo YouTube Channel: http://Youtube.com/MathMeeting Website: http://MathMeeting.com
Views: 217112 Math Meeting
Hi everyone. This video will show you how to calculate the correlation coefficient with a formula step-by-step. Please subscribe to the channel: https://www.youtube.com/frankromerophoto?sub_confirmation=1+%E2%80%9Cauto+subscribe%E2%80%9D https://goo.gl/aWzM8C
Views: 524367 cylurian
The National Institute of Nursing Research (NINR) Big Data in Symptoms Research Boot Camp, part of the NINR Symptom Research Methodologies Series, is a one-week intensive research training course at the National Institutes of Health (NIH) in Bethesda, Maryland. NINR's 2015 Boot Camp provided a foundation in data science focusing on methodologies and strategies for incorporating novel methods into research proposals. Since there was a high demand for the course, the first day of the Big Data Boot Camp was videocast live and is now available in segments on the NINR YouTube channel. To learn more visit www.ninr.nih.gov/bootcamp. In Part 4, Dr. Patti Brennan of the University of Wisconsin-Madison discusses Big Data in Nursing Research.
Views: 883 NINRnews
Last updated Summer 2016
Views: 737 GHC Libraries
__________________________________________________________ FREE NRSNG Nursing Resources: 50 Most Commonly Prescribed Medications - https://bit.ly/2nHIMcV Head to Toe Assessment - https://bit.ly/2vLYZ5A Nursing Care Plan Template - https://bit.ly/2Mh3rDo NRSNG Study Guides: Nursing Pharmacology Study Guide - https://bit.ly/2MhBRGe Fluid and Electrolytes Study Guide - https://bit.ly/2OIFy4t Nursing Lab Values - https://bit.ly/2P92U4p __________________________________________________________ FOLLOW ME ON SOCIAL: www.facebook.com/NurseBass1 www.instagram.com/Nurse_Bass www.twitter.com/Nurse_Bass __________________________________________________________ Valuing honesty and integrity, I am an Affiliate of NRSNG.com. Given this, I want you to know that there may occasionally be products or services offered on this channel from which I receive a commission if you make a purchase. You will receive a phenomenal piece of educational material and will help support this channel in the process. If you have any questions regarding the above, please do not hesitate to contact me via email. It can be found on my "About" page. __________________________________________________________ The views and opinions expressed on this channel and/or in the videos on this channel are that of myself and not of any educational institution. In compliance with HIPAA and to ensure patient privacy, all patient identifiers in all videos have been deleted and/or altered. The views expressed on this channel and/or in the videos on this channel are personal opinions. The information I present is for general knowledge purposes only.
Views: 110489 Nurse Bass
Making Sense of Medicare Data: From Mining to Analytics by Luc Pezet, Information Engineer, Archway Health Advisors accompanied by Dr. Flavio Villanustre, LexisNexis VP of Technology Architecture & Product (and former neurosurgeon) and Rodrigo Pastrana, Consulting Software Engineer Hosted by Eric David Benari A Database Month event http://www.NYCSQL.com/events/221524068/ Medicare's Bundled Payments for Care Initiative (BPCI) is the largest Medicare payment innovation program. Bundled payments involve paying a 'package price' for all the services required to treat an episode of care. Unlike the current 'fee for service' model, providers will assume financial risk and have financial incentives to improve efficiency and patient outcomes. Currently, more than 5,000 providers have applied to this program, representing $47 billion of Medicare spending. Archway Health Advisors is building a platform that helps providers like hospitals and nursing homes manage their bundled payments program. Analyzing complex Medicare claims payment data is critical to understanding the risks of participating in the bundled payment program. We are using the open source HPCC Systems platform to power the data management and analytics required to successfully manage the risks and look for care improvement opportunities. In this presentation, we will review our HPCC Systems implementation and provide some examples of the analysis that we are providing our customers. Luc Pezet, Information Engineer, Archway Health Advisors Luc Pezet is a Solution and Software Architect with over 10 years of experience in pioneering web analytic tools and complex data management projects. His expertise includes designing and implementing Big Data solution to process millions of data inputs on a daily basis to monitor, assess and improve performance. Luc is a successful entrepreneur and co-founder of Tripfilms, the largest database of travel videos on the web. He also has served as interim CTO for The Achievement Network (ANET), a non-profit education company that helps schools use assessment data to improve student performance. At ANET, he implemented web tools for staff to help scale their operations and end-user web sites for teachers and principals to access reports and analysis. Within just a few years, this platform has helped ANET grow from 13 schools in the Boston area to over 480 schools and 145,000 students across 10 states. ANET has been recognized as a pioneer in education innovation and was named 'New Schools Ventures Organization of the Year' in 2011. Luc holds a Master's Degree in Computer Science from Rennes University in France.
Download this Spreadsheet FREE: http://www.thenighttimeentrepreneur.com/staff-schedule/ Become an online entrepreneur - SUBSCRIBE to the Channel This video negates the need for an expensive scheduling software solution for your staff. All done with Microsoft excel, its a totally free and totally accurate way of scheduling your staff, not to mention how versatile it is to have the information in Microsift Excel. Gimme 1 Dolla! Become a Patron of mine! → https://www.patreon.com/tnte I will thank you a thousand times! Interested in using ZonPages for Amazon selling? → https://zonpages.com?aff=183811 My Social Media: Faceook → https://www.facebook.com/nighttimeentrepreneur/ Twitter → https://twitter.com/NT_Entrepreneur?lang=en I'm a Bluehost user, I love their hosting and ease of use! → https://www.bluehost.com/track/nte/ I bolt OptimizePress to my WordPress Sites! → https://zf137.isrefer.com/go/op/thenighttimeentrepreneur/ My Badass Microphone! - http://amzn.to/2ptx5IZ My 1080p Webcam! - http://amzn.to/2qmPpks If you can read this, SUBSCRIBE! how to make an employee schedule how to make a employee schedule on excel how to make an employee schedule that works how to make employee schedule using excel how to make a employee shift schedule how to make a monthly employee schedule in excel how to make a staff schedule in excel how to make a staff schedule employee scheduling software free employee scheduling software how to make a work out schedule how to make an employee quit legally how to make a work schedule on google calendar how to make an employee schedule best free employee scheduling software how to make work schedule for employees how to make work schedule on excel how to make a employee schedule how to make a employment verification letter how to make a verification of employment letter how to make an employment verification letter how to make an employee training manual how to make an employment letter how to make a work schedule calendar how to make a employee schedule on excel how to make an employee schedule that works how to make employee schedule using excel how to make a employee shift schedule how to make a monthly employee schedule in excel how to make a staff schedule in excel how to make a staff schedule
Views: 63760 The Night Time Entrepreneur
Hey everyone! Glad to be back! Decision Tree classifiers are intuitive, interpretable, and one of my favorite supervised learning algorithms. In this episode, I’ll walk you through writing a Decision Tree classifier from scratch, in pure Python. I’ll introduce concepts including Decision Tree Learning, Gini Impurity, and Information Gain. Then, we’ll code it all up. Understanding how to accomplish this was helpful to me when I studied Machine Learning for the first time, and I hope it will prove useful to you as well. You can find the code from this video here: https://goo.gl/UdZoNr https://goo.gl/ZpWYzt Books! Hands-On Machine Learning with Scikit-Learn and TensorFlow https://goo.gl/kM0anQ Follow Josh on Twitter: https://twitter.com/random_forests Check out more Machine Learning Recipes here: https://goo.gl/KewA03 Subscribe to the Google Developers channel: http://goo.gl/mQyv5L
Views: 206617 Google Developers
Advertisers and even the government are learning more about consumers through the process of data mining.
Views: 145 WLKY News Louisville
Authors: Joel Dudley, Icahn School of Medicine at Mount Sinai Ping Zhang, IBM Thomas J. Watson Research Center Fei Wang, Department of Healthcare Policy and Research, Cornell University Abstract: In the last decade, advances in high-throughput technologies, growth of clinical data warehouses, and rapid accumulation of biomedical knowledge provided unprecedented opportunities and challenges to researchers in biomedical informatics. One distinct solution, to efficiently conduct big data analytics for biomedical problems, is the application of matrix computation and factorization methods such as non-negative matrix factorization, joint matrix factorization, tensor factorization. Compared to probabilistic and information theoretic approaches, matrix-based methods are fast, easy to understand and implement. In this tutorial, we provide a review of recent advances in algorithms and methods using matrix and their potential applications in biomedical informatics. We survey various related articles from data mining venues as well as from biomedical informatics venues to share with the audience key problems and trends in matrix computation research, with different novel applications such as drug repositioning, personalized medicine, and electronic phenotyping. More on http://www.kdd.org/kdd2016/ KDD2016 Conference is published on http://videolectures.net/
Views: 714 KDD2016 video
The Medical Algorithms Company offers the word's largest platform of online medical calculators, algorithms, and clinical decision making tools for physicians and other healthcare professionals.
Views: 1893 Medical Algorithms Company
Useful materials for cover letter writing: • coverletter123.com/free-28-cover-letter-samples • coverletter123.com/29-tips-secrets-to-write-successful-cover-letter • coverletter123.com/free-32-resumes-samples • coverletter123.com/free-ebook-90-interview-questions-and-answers • coverletter123.com/top-12-secrets-to-win-every-job-interviews • coverletter123.com/top-8-interview-thank-you-letter-samples Job levels related: administrator, advisor, analyst, assistant, associate, clerk, consultant, coordinator, controller, engineer, executive, manager, officer, representative, specialist, supervisor, support, vp, director, leader, technician, entry level, senior , junior… The above cover letters can be used for fields such as: accounting, administrative, advertising, agency, agile, apartment, application, architecture, asset, assistant, audit, auto, automotive, b2b, bakery, band, bank, banquet, bar, benefits, beverage, billing, brand, budget, building, business, cafe, call center, car, catering, channel, clinic, commercial, communications, community, construction, consulting, content, creative, crm, customer relations, customer service, data, database, delivery, design, digital marketing, distribution, ecommerce, education, electrical, energy, engineering, environmental, equipment, erp, events, exhibition, export, f&b, facilities, factory, fashion, finance, fmcg, food industry, fundraising, furniture, gallery, golf, grants, grocery, gym, healthcare, help desk, hospital, hospitality, hotel, housekeeping, housing, hr, hse, hvac, ict, import, infrastructure, innovation, insurance, interactive, interior design, international, internet, inventory, investment, it, jewelry, kitchen, lab, leasing, legal, logistics, maintenance, manufacturing, market, marketing, materials, media, merchandising, mining, mortgage, music, network, new car, ngo, nhs, non profit, non technical, oem, office, offshore, oil and gas, operations, outbound, outlet, overseas, parts, payroll, pharmaceutical, pharmacy, plant, procurement, product, production, project, property, purchasing, quality assurance, r&d, real estate, records, recruiting, release, research, reservations, restaurant, retail, safety, dogcare manager, salon, security, service, shipping, social media, software, sourcing, spa, staffing, store, studio, supply chain, systems, technical, technology, telecom, telecommunications, tour, tourism, training, transportation, travel, vehicle, wealth, web, wedding, wine… Other topics: • cover letter examples • how to write a cover letter • cover letter template • cover letter for job application • how to make a cover letter • job application cover letter • cover letter tips • cover letter writing pdf download ebook
Views: 1698 Boo Lady
Center for Business Analytics, Co-sponsored by the College of Nursing, Analytics Research Briefing presents: "Predictive Analytics for Parkinson's Disease to Identify Risk Factors and Drive Patient Care" by Katrina Adams, PhD, Predictive Analytics Practice Lead LPA Software Solutions. Adams presents the results of a joint study with the University of Rochester Medical Center (URMC) to develop quantitative disease progression models for Parkinson’s disease using clinical data at the Medical Center. There are no proven therapies that can delay, stop or reverse the clinical or neuropathological progression of Parkinson’s disease. This is primarily because Parkinson’s disease is slow and heterogeneous in symptomatic progression. Katrina will describe the steps taken while building a model in an attempt to quantify and predict Parkinson’s disease progression, identifying patient attributes which may explain the heterogeneity of disease progression as measured by the Unified Parkinson’s Disease Rating Scale (UPDRS).
Views: 160 villanovauniversity
Resume is a document that speaks about You, and tells why an Employer should choose You for a job interview. Resume is reviewed before the job interview, so it is a reflection of yours as an ideal employee with desired qualification and experience. Some people stuff their resume with too much information, while others mention the specific information, but in an unorganized manner. So, it is very important to know the art of writing a good resume. Resume Service and examples are available for Resume Help. What it needs to make a Good Resume: -What Abilities You Possess, What Qualities You Have, and Your Achievements in Professional terms. -Your Previous Jobs, your Academic and Professional Qualification, etc in a chronological order (based on time period). We shall discuss above points in Resume Format and Resume Examples Sections also. RESUME TIPS Below are the tips to build a quality Curriculum Vitae: Use a Good A-4 Size paper. Use same Paper for Cover Letter also. Do not Fold your Resume sheets. Use the same Size Envelope, prefer White colored Envelope. Use Simple font of size 12 Points. Do not use more than two font styles in your Resume. Do not use any Symbol or Logo on the top of your Resume. You might think it looks attractive but it does not look professional that way. A Resume typically should be restricted to a page without any irrelevant details. Make sure you personalize your objective for each Organization, e.g. AIR HOSTESS WITH SINGAPORE AIRLINES, MARKETING EXECUTIVE WITH IBM CORP, etc. A Cover letter should be personalized to specific Organization, you wish to apply for. Do not list References, write instead that they are available on request. List the References only if specifically asked. Look for the Employer's needs. Portray Yourself as a Solution to their needs in your resume. Write Your Professional Qualifications and Knowledge first as this section tells the Employer about your Job skills. Then List your Academic Qualifications in chronological order, starting with recent Qualification to Previous ones. You may write your Qualification in order of Relevance, if Your Educational Background is not directly related to Your Job Skills. Write Your Experience in terms of Quantity if possible. Mention time Period of Work, How well you performed, Achievements in your performance, highlights o your Career graph. Use P-A-R Technique for stating your Experience. Mention Problem-Action-Result in your previous Employment. What were your responsibilities, How You executed your Responsibilities and What Results You Achieved. This Really impresses the Employer ! Get You Resume Reviewed by a Friend. This will help you to get feedback on the language and content of your Resume. Check for the Spelling Errors, Grammatical Mistakes, Punctuation Problems, Alignment etc. TSMadaan Motivational Speaker | Life Coach
Views: 198518 TsMadaan
Drs. Jonathan Nebeker and Sara Knight share their insights about how informatics and data mining in VA’s may be used to improve care for Veterans.
Views: 447 Veterans Health Administration
Incorporating information technologies and information management, this work describes evolving areas of efficiency in the healthcare industry due to healthcare informatics enhancements. Beginning with an overview of how information management can enhance organizational efficiency the book delves into how informatics can impact productivity for healthcare providers and reduce costs. It stresses the incorporation of available information technologies along with appropriate management tactics to ensure the most effective informatics outcomes that can drive efficiencies. Areas that are addressed include project management in healthcare, knowledge management, decision support systems, business intelligence, Six Sigma, and advanced analytics such as data mining.
Views: 150856 YouTube NJIT
This video covers calculation of Arithmetic mean ( from the Chapter Measures of Central Tendency ). Calculation of Arithmetic mean ( AM ) for ungrouped data and discrete data has been explained. The short cut method for discrete data has also been explained. Calculator trick to calculate AM has been explained. This video ( Statistics series ) is not class specific, I have tried cover all the details hence this lecture might be helpful for but not limited to - class 11 ( Statistics ), CA-CPT, CMA( foundation ), CS-Foundation, B.Com( H and P ), BBA, and various other competitive exams. If you liked the video please give it a thumbs up ( press the LIKE button ) and SUBSCRIBE to my channel. Thank You !! All the best :-)
Views: 466829 studyezee
From the January 2014 meeting of the National Advisory Council for Nursing Research.
Views: 1424 NINRnews
Data Analytics for Beginners -Introduction to Data Analytics https://acadgild.com/big-data/data-analytics-training-certification?utm_campaign=enrol-data-analytics-beginners-THODdNXOjRw&utm_medium=VM&utm_source=youtube Hello and Welcome to data analytics tutorial conducted by ACADGILD. It’s an interactive online tutorial. Here are the topics covered in this training video: • Data Analysis and Interpretation • Why do I need an Analysis Plan? • Key components of a Data Analysis Plan • Analyzing and Interpreting Quantitative Data • Analyzing Survey Data • What is Business Analytics? • Application and Industry facts • Importance of Business analytics • Types of Analytics & examples • Data for Business Analytics • Understanding Data Types • Categorical Variables • Data Coding • Coding Systems • Coding, coding tip • Data Cleaning • Univariate Data Analysis • Statistics Describing a continuous variable distribution • Standard deviation • Distribution and percentiles • Analysis of categorical data • Observed Vs Expected Distribution • Identifying and solving business use cases • Recognizing, defining, structuring and analyzing the problem • Interpreting results and making the decision • Case Study Get started with Data Analytics with this tutorial. Happy Learning For more updates on courses and tips follow us on: Facebook: https://www.facebook.com/acadgild Twitter: https://twitter.com/acadgild LinkedIn: https://www.linkedin.com/company/acadgild
Views: 252777 ACADGILD