Sentences with phrase «from normal distribution»

Maximum Likely Robust estimation (MLR) was used, as MLR gives the most accurate estimate of chi - squares when the distribution of scores deviates from a normal distribution (Satorra and Bentler 1994), which turned out to be the case for scores on our identity formation measure.

This is one reason why, despite claims in the media, we are not hitting any more all time daytime highs than we would expect from a normal distribution.

Also this is no different in hypothesis testing, it is quite routine to use a null hypothesis that we know from the outset is not true, for instance «the coin is unbiased» or «this is a sample from a normal distribution» (which is only actually true asymptotically).

The scenario I was imagining was that each observation had a number added to it that was drawn randomly from a normal distribution with a standard deviation of 10 degrees.

If these last two outliers were drawn from a normal distribution, each would have much less than a one - in - a-hundred chance of occurring in the entire 13.8 billion years the universe has existed.

If it were drawn from normal distribution, this would be a one - in -67-million-year event, like the one that wiped out the dinosaurs.

Not exact matches

Note: Shareholders receiving any income from the corporation are also subject to normal income taxes on corporate distributions and dividends.

Though these overall returns have been consistent with my expectations, the distribution of returns between falling markets and rising markets differs from what I would expect under normal valuation conditions.

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«Similarly, the cocoa mass spraying exercise was changed from the normal model of spraying by gangs to the distribution of sub-standard insecticides and fungicides to farmers to spray their own farms.

Using a mathematical model known as the Ising model, invented to describe phase transitions in statistical physics, such as how a substance changes from liquid to gas, the Johns Hopkins researchers calculated the probability distribution of methylation along the genome in several different human cell types, including normal and cancerous colon, lung and liver cells, as well as brain, skin, blood and embryonic stem cells.

In this particular case, the researchers used DESI mass spectrometry imaging to look at the distribution and amounts of fatty acid substances, called lipids, within breast tissue and normal tissue from 61 samples obtained from 14 breast cancer patients that underwent mastectomy.

The team calculated the black hole's distance from the core by comparing the distribution of starlight in the host galaxy with that of a normal elliptical galaxy from a computer model.

A) Venn diagram of the qualitative distribution of proteins identified in the pooled, immunodepleted, and fractionated cerebrospinal fluid (CSF) from normal healthy control subjects, Chronic Fatigue Syndrome (CFS), and Neurologic Post Treatment Lyme Syndrome (nPTLS).

Normal distribution of change in sugar intake from sweet food / beverages was verified using a histogram.

The Reverse & Battle Minigames qualify as Bowser Minigames due to the normal rules & Mini Star distribution changed from Bowser.

On average across middle and high school math, TFA teachers out - performed veteran teachers by 0.07 standard deviations, the equivalent of 2.6 additional months of instruction or helping a student move from the 27th to the 30th percentile on a normal distribution of test scores.

Benefit payments may not be made until the member has been terminated for 3 calendar months, except the college may authorize a distribution of up to 10 percent of the member's account after the member is terminated from employment with all Florida Retirement System participating employers for 1 calendar month if the member has reached the normal retirement date as defined in s. 121.021.

In normal circumstances, the drive torque distribution between front and rear axle can be set from 100:0 to 50:50.

Instead, the money that you have already spent will be recategorized from a normal HSA medical distribution to an excess contribution withdrawal.

These sections allow you to begin receiving money from your retirement accounts before you turn age 59 1/2 without the normal 10 % premature distribution penalty.

Federal regulations have not allowed pension distributions before a defined benefit plan's normal retirement age unless the worker separates from service.

Now if errors followed a normal distribution, a 95 % confidence interval on total returns would be plus or minus 3.8 %, i.e., from 1.0 % to 8.6 %.

The tax code allows up to $ 10,000 to be withdrawn from an IRA (Roth or regular) and put towards the purchase of a first home without having to pay the normal 10 % penalty for an early distribution.

According to PIMCO, the term new normal creates an environment where the consensus expectations has shifted from traditional bell - shaped curves to a much flatter distribution of outcomes with fatter tails.

In addition to the normal risks associated with fixed income securities discussed elsewhere in this SAI and the fund's prospectus (e.g., interest rate risk and default risk), CDOs carry additional risks including, but not limited to: (i) the possibility that distributions from collateral securities will not be adequate to make interest or other payments; (ii) the quality of the collateral may decline in value or default; (iii) the fund may invest in CDOs that are subordinate to other classes; (iv) the complex structure of the security may not be fully understood at the time of investment and may produce disputes with the issuer or unexpected investment results; and (v) credit ratings by major credit rating agencies may be no indication of the creditworthiness of the security.

Although the phenotypic distributions deviated from normal in all breeds and both traits, it is possible that the distribution of residuals is not very different from normal after fitting statistical models.

He took each proxy record (typically composed of values rising over time), treated it as a normal distribution, computed a standard deviation, and then divided the values from that proxy by its SD to yield «standardized» values.

The «basis» for linear regression is that if the noise (deviation from the model) follows the normal distribution, then linear regression is the maximum - likelihood solution for a straight - line fit.

The density of monthly means is not a normal distribution, neither from the separate datasets nor from the combined dataset.

At the low or middle range, a small shift still makes everything well within the normal distribution from the past but at the top end, the shift pushed events into new records and extremes.

If attempting to simulate from a multivariate standard normal distribution in a large dimension, when starting from the mode of the target, i.e., its mean γ, leaving the mode γis extremely unlikely, given the huge drop between the value of the density at the mode γ and at likely realisations Continue reading →

In climatology development of the average may differ substantially from the extremes — both as a characteristic of the normal distribution — and the possibility of skewness increases.

Demand response is a non-persistent intentional change in net electricity usage by end - use customers from normal consumptive patterns in response to a request on behalf of, or by, a power and / or distribution / transmission system operator.

To illustrate the implications, Weitzman notes that, when we run the climate models, a normal («thin - tailed») distribution of impacts from a doubling of atmospheric greenhouse gas concentrations above pre-industrial levels produces a median temperature change of 3 degrees Celsius with a 15 % probability of a warming above 4.5 degrees Celsius.

I haven't had the chance to read it, but as I understand it the authors fit a normal (or Gaussian) distribution to weather measurements from the 1950s to the 1980s, and then concluded that the current conditions in the midwest were too improbable to be natural.

We assigned each of the constraints a log - normal distribution from estimates in the literature, as detailed by Allen et al. [11].

If the modern fraction error is normally distributed, then the error distribution of the RC age is log normal — since the activity level over time is dictated by the well known «exponential decay» formula and the transform from modern fraction to time is logarithmic.

For a well - behaved, unimodal distribution, the vast majority of the data we have to look at will (by definition) come from near the mode where all distributions will look Normal.

How would one go about determining whether a «rare» event is actually a far from equilibrium effect like those described above and not simply a low probability event governed by the normal distribution?

I would observe that one gets normal distributions by additive combinations of random effects and lognormal (right skewed) distributions from multiplicative effects.

According to Fig 31 inthis «Jason» paper (pointed out on the «Harbinger» thread), for a normal distribution, such a 1 - sigma shift in the mean would increase the probability of an event with an initial 0.001 probability (roughly corresponding to an event that lies > 3 - sigma from the mean [probability 0.0013]-RRB- by a factor of about 20 or so.

Create a population of 7000 people (s = 1 to 7000) and independently draws two potential survey responses x and y (from standard normal distributions) for each of them.

From the close match to the IPCC's graph (see Figure 5, below) achieved using a normal error distribution, it is evident that the IPCC made a normality assumption, so that has also been done here.

It follows from Forster & Gregory's method and error distribution assumption that the PDF of Y is symmetrical, and would be normal if a large number of observations existed.

The combinded broadening from a normal speed distribution of molecules and the broadening due to the uncertainty principle is addressed in the Voigt temperature profile.

Looking at these results, that are admittedly anecdotal at this point, I see generally better fits to a normal distribution and lower autocorrelation (AR1) in the residuals as one goes from monthly to individual months to annual data series and as one goes to sub periods of a long term temperature anomaly series.

When Hansen looked at the data from 1951 to 1980, the distribution of data was very similar to a normal distribution.

1) I like the suggestion above of a Bayesian option: if I were to do this, I'd probably take a normal distribution centered on 0.2 degrees / decade as my prior (based on the AR4 model mean warming over the next couple decades... perhaps another option would be a flat distribution from, say, -0.1 degrees to 0.5 degrees), and then see how that changes with added data points.

But unlike the other distributions mentioned in earlier paragraphs, it is stable and so enjoys the i.i.d. property well known from the most popular of the stable distributions, the normal distribution.