Sentences with phrase «measurement error when»

~ Ordering custom minimizes the chance of measurement error when you have a workroom through an interior designer.

I would be much more inclined to believe it is a measurement error when dealing with such fine changes.

Not exact matches

The new measurement fits with previous estimates when their margin of error is considered, he says.

In addition, they estimate the impact of other sources of error on the mRNA and protein abundance measurements using direct experimental data, and they find that, when error is explicitly measured and modeled, an even greater correlation between mRNA and protein is expected.

When the discrepancy arose a few years ago, scientists suspected it would fade away, a symptom of measurement errors.

When Bailin deduced the angular momentum of the warped portion of the Milky Way's disk and compared that measure with SagDEG's angular momentum, he found that, within the margins of measurement error, the two angular momenta are very similar in strength and direction.

On top of that, rarely do these people accurately know their body fat percentages (other than very optimistic guesses) and even when measurements are taken almost all body fat estimation techniques (including skin-folds, BIA, etc) are subject to up to 4 % error.

But when you are extremely overweight, body fat measurements can be extremely prone to error.

Accordingly, and also per the research, this is not getting much better in that, as per the authors of this article as well as many other scholars, (1) «the variance in value - added scores that can be attributed to teacher performance rarely exceeds 10 percent; (2) in many ways «gross» measurement errors that in many ways come, first, from the tests being used to calculate value - added; (3) the restricted ranges in teacher effectiveness scores also given these test scores and their limited stretch, and depth, and instructional insensitivity — this was also at the heart of a recent post whereas in what demonstrated that «the entire range from the 15th percentile of effectiveness to the 85th percentile of [teacher] effectiveness [using the EVAAS] cover [ed] approximately 3.5 raw score points [given the tests used to measure value - added];» (4) context or student, family, school, and community background effects that simply can not be controlled for, or factored out; (5) especially at the classroom / teacher level when students are not randomly assigned to classrooms (and teachers assigned to teach those classrooms)... although this will likely never happen for the sake of improving the sophistication and rigor of the value - added model over students» «best interests.»

In 2000, a scoring error by NCS - Pearson (now Pearson Educational Measurement) led to 8,000 Minnesota students being told they failed a state math test when they did not, in fact, fail it (some of those students weren't able to graduate from high school on time).

Observers committed to reducing error should consider multiple measurements for teacher evaluation.Yes, Evaluations Can Be Fair and Accurate In this month's ASCD, Robert Marzano discusses ways to minimize error and maximize accuracy and fairness when principals, coaches, or other administrators are conducting classroom observations.

# 2) Error Coherence: When you combine a large number of those measurements to get an average answer, do all the errors «pile up» or do they tend to «cancel each other out» instead?

I make use of an automatic error measurement system that verifies any portfolio utilizing replacement assets accurately models the desired design intent, and every chart clearly calls out when returns are only estimated.

It's interesting to notice the same denier crowd «accidentally» neglects to mention the up to ~ 7 % measurement error in ice extent values at certain times of the year when trumpeting «record ice extent in Antarctica».

It is a little dangerous to project a trend from two points on a sine wave, especially when the measurements of the two points are subject to «error correction.»

Secondly, one of the thing I keep saying when people engage in mathematical calisthenics: «Central values without error bars are not measurements»:

The probability will be the error in the measurement of CS when and if this is ever done.

For real SST measurements some of the errors will be of the nice kind that obligingly diminish when averaged.

I think you are confusing the problem of calculating the error when the mariner takes 10 measurements at 100 locations at the same time (and estimates the average at that point in time), and making the same estimate when only 1 measurement is taken on that day at each location, and some of the locations were missed, and some measurements occured at 6.00, and some at 8.00.

The rules of statistics tell that independent errors of individual measurements cancel out, when the total number of measurements is large.

When the inter-methodological (+ / --RRB- 2 C noted by Bemis, et al., is added as the rms to the average (+ / --RRB- 1.25 C measurement error from the work of McCrae 1950 and Bemis 1998, the combined 1 - sigma error in determined T = (+ / --RRB- sqrt (1.25 ^ 2 +2 ^ 2) = (+ / --RRB- 2.4 C.

When an anomaly calculated using normal means and data that are contaminated with systematic error, the error in the anomaly is (+ / --RRB- sqrt -LSB-(error in normal) ^ 2 + (error in the measurement) ^ 2].

I will update this when new data becomes available and will also attempt to demonstrate that the net slopes we see are within the margin of error for the measurement in a future post.

How can Trenberth publish that «the models match the TOA energy balance» when the measurement error on the TOA balance is ~ 5W / m ^ 2?

Let us simplify the problem further and assume that the lab can estimate the RC age on a sample (given an assumed initial mass fraction) with negligible error, and then consider how we generate the probability distribution for calendar date even when we have no laboratory measurement error to take into account.

P (Obs calendar - age = y) does not change much when y changes by a small amount, small enough that the carbon - 14 age changes by much less than the standard deviation of the measurement error.

Indeed this should always be done, because the noise is measurement error, which also biases estimates — unless it is appropriately accounted for, as it can be when retests occur in the survey.

Also: any idea how the estimator performs when subject to noise (e.g. measurement error)?

Later, when the signal is extracted from the random noise, from the measurement error and the deliberate measurement errors, and all of that extracted from the millennium temperature changes, can the «chicken and egg» relationship be considered.

When I subtract today's temp from from yesterday's that too has + / -0.02 error, but when I subtract tomorrow's temp from today, both differences both can't have the worst case error, the longer the string of days is the smaller the measurement errorWhen I subtract today's temp from from yesterday's that too has + / -0.02 error, but when I subtract tomorrow's temp from today, both differences both can't have the worst case error, the longer the string of days is the smaller the measurement errorwhen I subtract tomorrow's temp from today, both differences both can't have the worst case error, the longer the string of days is the smaller the measurement error is.

When I simulated how many times would actually measured random value would be indeed true highest value (sd = 0.7 was 0.7 for value and 0.5 for a measurement error, both normally distributed), I've got the following results (Number of years, being highest percentage): 2, 0.801146 10, 0.532256 20, 0.46076 50, 0.384286 100, 0.338422 135, 0.32037 200, 0.30028 1000, 0.232482 10000, 0.165234 I am not sure, but can we conclude that 38 % likelihood was actually not that small?

But when you write in a post here at WUWT, «The problem of «extra heat» in land temperatures (likely to be UHI and more) is escalated by GISS because they extrapolate the ground based land temperature measurements over the oceans in stead of using real ocean data,» I will remind you that GISS notes the errors in the dTs data on their webpage: