Sentences with phrase «statistical model worked»

Not exact matches

Hansen's seminal work essentially updated an important theory of statistical modeling from the late 1800s, called the Method of Moments, allowing it to be used more accurately for things like setting monetary policy.

Medicines that are personally tailored to your DNA are becoming a reality, thanks to the work of U.S. and Chinese scientists who developed statistical models to predict which drug is best for a specific individual with a specific disease.

Ms Koechlin, Professor Philippe Autier and colleagues used statistical models to work out whether current cancer death rates were due more to the effects of age, the year of birth (which takes into account exposure to cancer - causing agents such as sunshine during early life), or to the recent introduction of new medical technologies or treatments.

«The dilemma for science is that you're always working with imperfect data and imperfect statistical models,» Donohue said.

«We believe that the analytical results and insights we obtained in this work have broader implications for timing phenomenon in chemical kinetics, ecological modeling and statistical physics.»

Her work focuses on supporting the efforts of law enforcement groups and nonprofit organizations by using statistical models to monitor human trafficking.

And since these statistical models appear to work most of the time, efficiency rises and profits surge.

She applauds the new work, noting that Ludwig and colleagues used apt statistical models to try to avoid confounding effects and excluded subjects with other risk factors such as gestational diabetes or extremely high birth weight.

Since math and stats are my passion, and since my deep connection to my work derives from the fact that I instinctively and reflexively see my world as one giant statistical model, it's no surprise that my creative forms of expression often take some sort of math / stat form.

Her technical work has contributed to validity theory, standard setting, and statistical models for detecting test bias.

The idea behind value - added modeling is to level the playing field by using statistical procedures that allow direct comparisons between schools and teachers — even when those schools are working with quite different populations of students.

APA has expertise in a wide range of approaches that we leverage in conducting our work, including: data analysis, cost modeling, statistical modeling, surveys, interviews, focus groups, facilitation, and literature reviews.

If the statistical model is based on good background information, such as prior test scores that strongly predict future test scores, this may work very well.

The primary requirements of the work are (a) professional competence in applying the theoretical foundations of computer science, including computer system architecture and system software organization, the representation and transformation of information structures, and the theoretical models for such representations and transformations; (b) specialized knowledge of the design characteristics, limitations, and potential applications of systems having the ability to transform information, and of broad areas of applications of computing which have common structures, processes, and techniques; and (c) knowledge of relevant mathematical and statistical sciences.

The CFP standard is high and requires a bachelor's degree, at least three years of relevant work experience and passing a wide number of exams on statistical modeling, insurance, taxes, and investments.

These same analysts then get surprised when the model doesn't work when applied to the real markets, because of the calculated relationship being a statistical accident, or because of other forms of implementation shortfall — bid - ask spreads, market impact, commissions, etc..

DDS: OK, who do you think is more likely to be right - thousands of experts, familiar with the data, methods and models of a field, with combined experience into millennia, actively working each day to understand and advance the field and who all agree based on the evidence — or - Some random jerkwad on the Intertubes who doesn't even know the difference between a statistical and a physical model?

I worked in the financials industry 90 — 96, then in supply chain from 98 — 01, now I'm in the clinical trials industry (but not coding anything to do with statistical models); so, I find it interesting that we can use such tools to make linkages like are reported for climate.

I'm a software developer and I've worked with statistical models (not creating them, just coding them as specified by the actual statisticians).

-- in which case, that's a statistical model prediction, which, at least in this context, we shouldn't rely on — if we actually know some things about how the climate works then it makes more sense to use that knowledge.

This is not a very strong statement though, and more work could perhaps be done to construct a better forecast using the underlying trends in the models and statistical models for the ENSO and internal variability components inferred from observations, rather than purely from model realisations.

A statistical model (based on the work of Judith Lean at the Naval Research Laboratory) that accounts for solar variability, El Niño, volcanic activity, and greenhouse warming indicates that the underlying trend of global warming has accelerated over the past 15 years.

Over at Amazon UK, Rudy Manchego, who works with statistical models and knows whereof he speaks, writes:

Working under the supervision of the Research Climatologist, the Statistical Modelling Analyst will analyse and model regional climate data as part of a multi ‐ disciplinary team consisting of PCIC climatologists and research collaborators.

Conversely, in the absence of answers to these questions, the work is destined to languish as one more purely statistical / phenomenological climate model that can not readily be distinguished from hundreds of such climate models already in the literature.

I work with t tests, Chi square, Z scores, linear regression, multiple regression, multi level modeling, ANOVA, MANOVA, and other statistical techniques.

Having done various sorts of modeling (simulation, population models, stability analyses, fractal models, statistical models) and having seen people who just throw any old equation in to make something work, I don't believe anything about a «model» unless there is a clear explication of it and unless it works well.

Personally, I think statistical models for seasonal sea ice forecasts will work better in the short term.

Empirical models work with real measurements where every variable has a range of normal values within a given statistical distribution.

Anybody who takes Webs criticism of statistical methods need only to go to his blog, examine his CSALT model for a little while, and wonder to themselves why he thinks that he can use a curve fitting method that works, for example, for a jet engine part, and apply it to an open, complex natural system.

Several models are created (in fact not a few of the dynamical El Nino models have GHG influences calculated in), each with its own set of «how climate works» mathematical scenarios, which are then compared to the statistical models.

Although climate models work best with the addition of CO2 as a forcing, to statistically determine causation, a cointegration statistical approach is necessary to observe the CO2 signal.

Working from a set of projections from eight different global climate models being driven by three different emissions scenarios, the authors used statistical downscaling to drive a hydrology model to determine what changes could be seen to the hydrology of these regions.

PA Reps for staff development and growth opportunities * Plan, assign, and direct work, appraise performance, reward and discipline employees, address complaints and resolve problems within the team * Assist in the hiring process * Assist in the preparation of performance reviews * Deliver performance reviews in conjunction with the Prior Auth Manager * Meet monthly with each staff member to go over performance status * Assist with training as needed * Lead weekly Team meetings with staff to keep them informed of changes to policy and procedures and corporate communications * Meet with the Prior Authorization Management team weekly to report on clinical call center performance and personnel issues Required Qualifications: * High School Diploma or equivalent * Current and unrestricted Pharmacy Technician license * 2 years» experience supervising Pharmacy Technicians in a Call Center environment * Prior Authorization experience * Knowledge of the Pharmacy Benefit Management and / or Health Insurance * Knowledge of Call Center industry through work experience and as obtained through related courses * Proficient in Microsoft Word and Excel Preferred Qualifications: * Bachelors» Degree * PBM experience * National Pharmacy Technician Certification Required Competencies: * Must have strong leadership and problem solving skills * Strong written and verbal communication skills * Strong interpersonal skills * Ability to effectively present information and respond to questions from groups of associates, managers and clients * Ability to comprehend ACD statistical reporting and apply it to the operation of the department * Ability to interpret a variety of instructions furnished in written, oral, diagram or schedule form * Ability to maintain a high level of consistency while working with team members * Ability to recognize the needs of the staff, heighten morale, and decrease stress and burnout * Ability to understand what style of conflict resolution is best suited for a particular situation * Ability to determine the needs of each individual team member and assist them in achieving set goals * Demonstrate a clear understanding of company and client confidentiality * Excellent organizational skills * Exemplary coaching / motivational skills at both an individual and team level * Adaptable and able to move with change while maintaining a positive attitude and strong role model for the Team.

I also work as part of research team to develop predictive models in equity and commodities prices, volatilities and correlations using mathematical and statistical...

Gottman has been criticized for describing this work as accurately predicting divorce, when generally this work involves simply fitting statistical models to a data set, not making predictions about events in the future.