Sentences with phrase «using various data points»

Not exact matches

When we were discussing various data points in our mock meeting last week, a couple members brought up stats from other sources, and real committee chair Jeff Long stopped us from using them.

This software determines whether a defendant will commit a crime within the next two years based on six defendant features — although what features COMPAS uses and how it weighs various data points is a trade secret.

While the scattered data by themselves are invaluable, separate data points are hard to interpret, as different methods used at various sites can obscure larger patterns.

The floating platform allows the researchers to collect data using the canister at various points all along the river.

He has designed specialized software that biologists use to interpret the billions of data points generated by various genomic methods.

In all entry points, buttons provide a «Description» of how the data have been organized and the «Methods» used to construct the various tools.

While students and educators will nd themselves at various points on the journey, the end game is that learners can confidently use digital systems to ethically, safely and respectfully communicate data as information, and apply systems thinking to analyse, predict and shape system interactions that will positively and sustainably impact the lives of those around them.

First of all, I want to point out that this isn't my opinion — the list is compiled using various data sources from Statistics Canada, various real estate boards, environment Canada, Canadian Medical Association and FP Infomart's Canadian Demographics.

They do this by having a thorough application so they can check various variables and data points and use these to predict what your finances will look like.

Inspired by the facial recognition techniques and algorithms currently in use in various public and private enterprises, including social media, Oursler employs a web of geometric designs, scattered data points, and various registration nodes integral to the composition of each work.

While this methodology doesn't eliminate your point that the trends from different periods in the observed record (or from different observed datasets) fall at various locations within our model - derived 95 % confidence range (clearly they do), it does provide justification for using the most recent data to show that sometimes (including currently), the observed trends (which obviously contain natural variability, or, weather noise) push the envelop of model trends (which also contain weather noise).

In fact, this overweening clamor for raw data seems to miss the obvious point that if Mann or Briffa or the legions of others working in this arena are so wrong in their conclusions, it should be an easy task to disprove their claims using various experiments entirely independent of the data in question.

The way I see it, if you get various data points of ocean heat content, you then have to plot a trend to see how that is changing with the other changes in incoming and outgoing radiation and greenhouse gases andland use etc..

He cites unscientific rubbish (e.g. papers in Energy & Environment), uses outdated data, makes unsubstantiated and often demonstrably incorrect claims (e.g. about volcanoes producing more C02 than humans), uses various talking points that have been debunked long ago e.g. no warming for 10 years, NASA now claims the 30's were hotter — stuff that should be obviously wrong to anyone with a bit of scientific literacy.

I have questions about the use of change point algorithms that have not been answered to my satisfaction to date and I have a great deal of interest in the benchmarking of these various algorithms by testing against realistic simulated data where the truth is known.

I'm really big on data, so I provide my agents with various worksheets they can use to import information from the MLS to not only make it more digestible for the consumer, but also to make it easier for the consumer to understand specific neighborhoods or price points.