Sentences with phrase «data about correlation»

Because the game's main goal is to analyze data about correlation perception, the more people play, the more data is generated.

Researchers surveyed 138 pre-service generalist teachers in Australia in two university classes in 1998 and in 2008 and gathered data about the correlation between students» perceived music background and their confidence teaching music.

Not exact matches

The researchers compared egg shape with lots of data about each bird species, but found no correlation with clutch size, environmental factors or nest characteristics.

Researchers were particularly pleased about the direct correlation of mouse and patient data.

Correlations among the three data sets revealed that temperature deep in the mantle varied between around 1,300 and 1,550 degrees Celsius underneath about 61,000 kilometers of ridge terrain.

The data necessary to answer myriad questions — about, say, the correlations between the industrial use of certain chemicals and incidents of disease, or between patterns of news coverage and voter - poll results — may all be online.

Actually Blue Brain is very much about reverse engineering, looking at all the data, standardizing the data, getting the information into a framework where we can even do correlation - based science on it, building automatic tools to synthesize those data into biological phenomena.

Pfizer is using Semantic Web technologies to mesh data sets about protein - protein interaction to reveal obscure correlations that could help identify promising medications.

The genetic data, which includes about one million markers across the genome, is compared among individuals, among populations, and between current and ancestral populations to determine hidden patterns of relatedness, sort individuals into groups that share genetic characteristics, and find correlations with genes of medical relevance.

I present a case in my response that: 1) it is not appropriate to assume a linear correlation between the mutation rate on the autosomes and the mutation rate on the Y chromosome; 2) the mutation rate Mendez et al. computed for the Y from autosomal data is an order of magnitude lower than the mutation rate that was measured for the Y chromosome from a pedigree analysis in 2009; 3) the resulting TMRCA is inconsistent with what is known about diversity on the mtDNA, autosomes and X chromosome.

«Recent data have described a correlation between the levels of activated Notch1 and poor prognosis in a cohort of NSCLC patients, but only in patients with wild type p53,» a group that they wrote represents about half of all NSCLC patients.

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But, here is a big data nerd caution: even though there seems to be a correlation, we don't know about causation!

What this means in practice is that when correlations are this «weak,» it is reasonable to say statements about averages, for example, that «on average» as one variable increases the mean of the other variable increases, but it would not be prudent or wise to make predictions for individuals based on these data.

But for the purposes for which teacher - level value - added is currently being used, correlations above r = +.70 / r = +.80 would (and should) be most desired, and possibly required before high - stakes decisions about teachers are to be made as based on these data.

Steven Saus presents Measure Twice, Register For an ISBN Once (and Where Bowker's Data Reveals A Surprising Correlation About Smashwords) posted at ideatrash, saying, «One of the downsides of easy self - publishing is the difficulty drawing lines.

It is an apt metaphor because constructing an «optimal» portfolio based on * past * return, SD, correlation data tells us very little about the future.

«Guess the Correlation» is a human - based computation game that, while mildly entertaining, its main focus is on collecting information about how people perceive correlated data in scatterplots.

Statements about what apparently cointegrated data must do are based on infinitely long time series, while actual time series are finite, and with plenty of auto - correlation and so the «true» level of cointegration is not that certain.

The idea is obvious, but keeps getting proposed because those who propose it are pretty clueless about climate and get sucked in by correlations in tricky data.

We have far more data about increasing CO2 than increasing water vapor, hence if we want to test this hypothesis by looking for a correlation between global warming and the combined effect of CO2 and H2O, a correlation with CO2 alone is more feasible than one involving water vapour.

This data shows that the tree rings have a correlation with local temperatures that is much less than the rings have with hemispheric temperatures (explaining only about half as much of the variation).

The correlations are about as good for global and for hemispheric averages, but that may be partly due to limited data from SH.

I don't care what physicists say about CO2, historical & modern data says there is no correlation between atmospheric CO2 levels & temperature, except in that warming raises CO2 levels.

I wonder what is so complicated about the point that you can not select data based on correlation.

An analysis of the historical data suggests a strong correlation between the solar activity and the natural climate variations on centennial time - scales, such as the colder climate during the Maunder (about 1650 − 1700 AD) and Dalton (about 1800 − 1820 AD) minima as well as climate warming during the steady increase in solar activity in the first half of the twentieth - century (Siscoe 1978; Hoyt & Schatten 1997; Solomon et al. 2007; Gray et al. 2010).

So when the Usoskin 2005 abstract says: The long - term trends in solar data and in northern hemisphere temperatures have a correlation coefficient of about 0.7 - 0.8 at a 94 % — 98 % confidence level.

This site also has impressive tutorials about normalization of tree - ring data, dating tree - ring series using correlation analysis, and the creation of reference chronologies.

This may be totally off, since I know squat about climate science & the high - powered statistical programs used, but when there is a dearth of data in the social sciences (not enough to give low enough p values on correlations & regressions, simply due to small numbers of data, which is sometimes due to loading in too many control variables), we sometimes turn to chi - square & log - linear analysis to see if actual data reveal patterns incongruent with expected patterns.

The ABA's Bar Passage Data Spreadsheet should put to bed, finally, any doubts about the correlation between LSAT scores and bar passage rates, and provides strong support for the ABA's recent enforcement actions against law schools with exploitative admissions standards.

Lack of objective data becomes especially problematic when information about parent involvement and child achievement outcomes is reported by the same person; the result can be a distortion of the statistical relationships obtained, producing stronger correlations between the two than would otherwise be the case.

If you have any questions about posting, correlations, statistical nerdery, or have some ideas for other data studies we should run, let me know!