Sentences with phrase «best statistical test»

The best statistical test of an observation is to see if it has happened naturally in the past.

Now assume on the best statistical tests we get the surprising result that the series post-forcings continues to be stochastic.

Not exact matches

Subramanian tested the relationship between P / E and the 12 - month returns using R 2, a statistical measure that reveals how well a regression line — the line of best fit you see — explains the relationship.

A review of the various statistical tests, applied to the record of this period, of these 24 forecasters, indicates that the most successful records are little, if any, better than what might be expected to result from pure chance.

This paper examines the day of the week effect in the crypto currency market using a variety of statistical techniques (average analysis, Student's t - test, ANOVA, the Kruskal - Wallis test, and regression analysis with dummy variables) as well as a trading simulation approach.

The «soft» social sciences, which includes spirituality as well as psychology and sociology, rely on the statistical evidence that has been tested in the crucible of human experience.

As 2 - way is considered, I would say level of accomplishment (though Mikal has been the best defender on the team for the last two years and has an award to show for it last year BEDPOY if I am not mistaken) is not as relevant as it is to the GOAT discussion (though clearly still a factor), and rather, the eye test / statistical analysis is more applicable.

Other campaigns had cumbersome sign - up processes, weak subject lines and overly long messages that buried the ask, problems that user - testing and statistical analysis should be able to correct (i.e., segment your list, run several different subject lines and see which ones work best, something that nonprofit fundraisers and advocacy experts have been doing for years).

The researchers used over 300 statistical relationships to test if models integrating hydrology (hydroclimate - oriented models, including, e.g. recharge, H - CLIM) would perform better than models using climate only (climate - oriented models, CLIM).

Using clever statistical tests called mediation analyses to look at these interactions, the researchers found that aerobically fitter older men can perform better mentally than less fit older men by using the more important brain regions when needed.

In order to better understand how soil microbes respond to the changing atmosphere, the study's authors utilized statistical techniques that compare data to models and test for general patterns across studies.

«Our results show a clear statistical correlation between a high level of language competence and a good working memory in the students we tested,» she says.

They have developed a set of tools that can be used to make accurate, rapid assessments of proposed materials, using a series of relatively simple lab tests combined with computer modeling of the physical properties of the material itself, as well as additional modeling based on a statistical method known as Bayesian inference.

To develop a clinical decision rule for acute bacterial rhinosinusitis, Ebell needed to determine which combination of symptoms and tests best predicted the presence of bacteria and compare the statistical predictor to a reference standard, which is used to confirm its accuracy.

Yesterday, at a meeting in Washington, D.C., a pair of well - known researchers, Michael Robbins and Noble Kuriakose, presented a statistical test for detecting fabricated data in survey answers.

The report's conclusions about the importance of teacher quality, in particular, have stood the test of time, which is noteworthy, given that today's studies of the impacts of teachers use more - sophisticated statistical methods and employ far better data.

However, a poorly designed scheme, which ignores the statistical properties of schools» average test scores, may do more harm than good.

To measure the effect on children's test scores of switching to a private school, we estimate a statistical model that takes into account whether a child attended a public or a private school, as well as baseline reading and math test scores.

There are several different statistical tests you can use, and the best one to pick will depend on the type of data you are dealing with.

Even if teachers are not sufficiently aware of the statistical forces at work to recognize their rather limited influence on test scores in the short run, they may well become aware of this over time.

A successful undergraduate teacher in, say, introductory biology, not only induces his or her students to take additional biology courses, but leads those students to do unexpectedly well in those additional classes (based on what we would have predicted based on their standardized test scores, other grades, grading standards in that field, etc.) In our earlier paper, we lay out the statistical techniques [xi] employed in controlling for course and student impacts other than those linked directly to the teaching effectiveness of the original professor.

Based on a series of experiments, [5] simulation studies, [6] and statistical tests, [7] elementary school value - added models do seem to address the selection bias problem well, on average.

Like teacher ratings, ratings of principals that are not based on statistical analysis of test scores tend to have little differentiation, with a Lake Wobegon effect in which everyone looks good.

Introduction, Brief Overview of Findings, The Parent Survey, Questionnaire, Interviews, Academic Test Scores and Accountability, Document Review, Parent Survey, Introduction, Statistical Analyses, Quality of the curriculum, Structure of the program, Negative public school experiences, Cost, Family values, Best Part about Participation, Quality curriculum, Flexibility, Teacher support, Pacing, Ready to use, Improvement, Additional Comments.

According to the report, «value - added models» refer to a variety of sophisticated statistical techniques that measure student growth and use one or more years of prior student test scores, as well as other background data, to adjust for pre-existing differences among students when calculating contributions to student test performance.

Sometimes districts make the mistake of saying, «Let's see if overhauling the HR department has an effect on student test scores,» when that link is tenuous at best, even using state - of - the - art statistical methods.

Because student performance on the state ELA and math tests is used to calculate scores on the Teacher Data Reports, the tests are high - stakes for teachers; and because New York City uses a similar statistical strategy to rank schools, they are high - stakes for schools as well.

Although value - added is one of the more advanced statistical approaches, researchers have raised concerns about its reliability, as well as potential unintended consequences, such as demoralizing teachers and placing greater emphasis on standardized tests.

They also omit the fact that there actually was good reason to question this year's scores, with 14 out of 14 states using the Smarter Balanced English language arts tests showing no gains — a significant statistical curiosity.

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.

For each of the characteristics they examined, McLean and Pontiff conducted two statistical tests to see how well they predicted future stock returns.

There are statistical tests that have been done that show that CAPE works best.

But you've known for, well, years now that what you claim you see, and what the statistical tests return, don't agree.

A third is that scientists in highly specialized fields would do well to reach out for added statistical expertise when trying to test broader implications of their work.

Why don't you suggest a test, and we'll put your statistical model up against the GCM output and we'll see who has the best match against the 20th C data.

Canadian Ice Service, 4.7 (+ / - 0.2), Heuristic / Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictors.

And as I wrote, seemingly minor changes in the details of the statistical algorithm (long memory model of natural variation vs short memory model; p = 0.01 instead of p = 0.10 [with its well - known high type 1 error rate in settings of multiple testing]-RRB- produce dramatically different inferences based on the time series of summary statistics.

it is important to recognize that an inherent difficulty of testing null hypotheses is that one can not confirm (statistically) the hypothesis of no effect.While robustness checks (reported in the appendix), as well as p values that never approach standard levels of statistical significance, provide some confidence that the results do not depend on model specification or overly strict requirements for statistical significance, one can not entirely dismiss the possibility of a Type II error.

Canadian Ice Service; 5.0; Statistical As with Canadian Ice Service (CIS) contributions in June 2009 and June 2010, the 2011 forecast was derived using a combination of three methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic Multi-Year Ice (MYI) extents, as well as an examination of Surface Air Temperature (SAT), Sea Level Pressure (SLP) and vector wind anomaly patterns and trends; 2) an experimental Optimal Filtering Based (OFB) Model which uses an optimal linear data filter to extrapolate NSIDC's September Arctic Ice Extent time series into the future; and 3) an experimental Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere, and sea ice predictors.

Canadian Ice Service, 4.7 (± 0.2), Heuristic / Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice Statistical (same as June) The 2015 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness extents, as well as winter Surface Air Temperature, Sea Level Pressure and vector wind anomaly patterns and trends; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent timeseries into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictors.

She had the space to do so, but instead hypothesized that science (and presumably climate science) bases its approach to statistical testing in the long shadow of its ancient historical ties to religion, which is something she may well be able to offer an opinion about, as an historian, but which has minimal relevance to policy makers or the interested public in interpreting scientific claims as found, say, in the IPCC reports.

Data were first examined for inhomogeneities using a statistical test to determine whether the data was fit better to a straight line or a straight line plus an abrupt step which may arise from changes in instruments and / or procedure.

As with previous CIS contributions, the 2016 forecast was derived by considering a combination of methods: 1) a qualitative heuristic method based on observed end - of - winter Arctic ice thickness / extent, as well as winter surface air temperature, spring ice conditions and the summer temperature forecast; 2) a simple statistical method, Optimal Filtering Based Model (OFBM), that uses an optimal linear data filter to extrapolate the September sea ice extent time - series into the future and 3) a Multiple Linear Regression (MLR) prediction system that tests ocean, atmosphere and sea ice predictors.

This assumed covariation has been demonstrated incompatible with the data series of T (t) an [CO2](t); the only possible correlation is between d [CO2](t) / dt and T (t) according to statistical tests well known in econometrics

ANSWER: Observations are the time series T (t), [CO2](t) and emissions (t); as d [CO2] natural (t) / dt correlates with T (t) and as no other correlation is (mathematically) allowed (by statistical tests) then the [CO2 natural] is, as shown as well on figure 17 - B, a consequence of the past temperatures (their time integral) and can not be their cause.

As for population homogeneity, the modern replication of Yamal is justified by the sensitivity analysis above based on Esper's tests for sample depth as well as the statistical analysis of Bunn.

If that summary is correct, I would think, that to continue these analyses in a meaningful way and assuming that the details of the more recent RCS algorithms will not be forthcoming, why not use a consensus (amongst our statistical minded participants here) best approach growth algorithm and see what kind of Yamal series results and how well it performs through sensitivity testing.

It gives up the high ground (even though one is using it for a good purpose, trying to argue that this «ensemble» fails elementary statistical tests.

The Bureau's use of statistical tests that are most likely to identify artificial discontinuities in the temperature data, and how they should be applied, are informed by well - established studies on observational climate data.

While the average soldier may not be carrying around the statistical 27 pounds of rechargeable batteries for a 72 hour mission all the time this announcement still may come as good news to those who do: Dupont and SFC Smart Fuel Cell AG have announced that their M - 25 portable fuel cell has now been deployed for limited testing with the U.S. Army.