Sentences with phrase «of regression to the mean»

The great leader understands the statistical concept of regression to the mean.

The most modest interventions should've helped, not to mention the statistical phenomenon of regression to the mean.

Then there might be some protection on the downside with some undetermined probability, however slight, of regression to the mean in terms of earnings.

In essence, all that's happened here is the rediscovery of the principle of regression to the mean.

We also carried out analyses to examine the effect of potential influence of regression to the mean arising from the fact that high injury numbers might have been a factor in the decision to implement a 20 mph zone in some areas.

Not exact matches

Over a long enough time period such effects tend to cancel out (a phenomenon called «regression to the mean»), thus it is unlikely that a firm is consistently high performing just because of chance events.»

With so many cheap stocks to choose from in 2009, even value managers who didn't want to buy financials could easily build a portfolio full of cheap stocks and wait for regression to the mean.

«It bears repeating that most investors extrapolate past performance, expecting the continuation of trends rather than the far - more - dependable regression to the mean.

Jung has seen that psychologically this means that an overemphasis on either side of a polarity such as conscious - unconscious, or sacred - profane, will lead not to a dialectical coincidentia oppositorum but to a reinforcement or enantiodromia of the (untransfigured) other pole, that is, to an inundation or regression.17 It will be helpful to keep these Jungian motifs in mind as we explore the somewhat surprising parallels between Jung's notion of «individuation» and Altizer's idea of an ongoing kenotic incarnation.

From what has gone before, the meaning of «its own realization» is obviously a part of what has been characterized as «ideal» realization, which was seen to be linked to conceptual regression (cf. PR 87 / 134).

This means distinguishing between healthy and unhealthy aspects of a person's religion; recognizing both the existential and pathological sources of anxiety, the significance of religious defenses, regression, and growth; and giving whatever encouragement he feels is indicated to positive religious directions.

When you cut through the chaos and look through the clear eyes of objective data, Game 4 was the ultimate regression to the mean.

A home - heavy schedule, excellent basketball by Bradley prior to an enormous regression to the mean, excellent basketball from Tobias before a similar but substantially smaller regression, hot shooting by Tolliver, Ish (for him) and Galloway, an offense that opponents hadn't already totally figured out, and overall solid health (sans perhaps Bradley's pre-absence groin injury, which was of unspecified severity).

But considering how poor this unit was for much of the year, we'll assume improvement, from a progression - to - the - mean standpoint, is more likely than regression.

But all of that changed when he hit the four - month mark, and I was forced to learn the true meaning of the term «4 - month - old baby sleep regression.»

We also estimated relative indices of inequality (RII) and slope indices of inequality (SII) as summary measures of relative and absolute inequalities of breastfeeding outcomes, respectively, across the entire distribution of maternal education.24 For child IQ, linear regression analyses using GEEs were performed to estimate mean IQ differences in lower maternal education from the reference category in each intervention group and compared between the groups.

Meta - regression was also used to establish whether mean concentrations of total cholesterol in each study had any effect on mean differences between feeding groups.

If a process is meant to improve the integrity of the electoral process, judgments that shoot it down can not advance the cause of our development; it means we have chosen a path of regression to the era where elections are decided by unsavory self - help in bloating the voter register with strange names on the part of politicians.

Some online dating sites offering compatibility matching methods use the word similarity as: «a proprietary Dyadic Adjustment Scale», others mean: «a proprietary multivariate linear regression equation», some say a mix of similarity and complementarity meaning: «a proprietary multivariate logistic regression equation», still others mix similarity and complementarity meaning: «a proprietary equation to calculate «compatibility» between prospective mates!»

To complete the task cards students will use knowledge of linear regressions (line of best fit, least squares regression), correlation coefficients, and calculating residuals and their meaning.

Regression to the mean can not explain the gains of high - scoring F schools relative to low - scoring D - schools because both groups begin with similarly low scores.

Statisticians explain the changes, regardless of direction, by claiming «regression to the mean.»

Discuss the idea of «regression to the mean» as it applies to schools.

We also find that high - performing teachers» value - added dropped and low - performing teachers» value - added gained in the post-move years, primarily as a result of regression to the within - teacher mean and unrelated to school setting changes.

They play the game of relative value, by using strategies such as regression to the mean.

It is a book about why long - term investing serves you far better than short - term speculation; about the value of diversification; about the powerful role of investment costs; about the perils of relying a fund's past performance and ignoring the principle of reversion (or regression) to the mean (RTM) in investing; and about how financial markets work.

Or perhaps a flood of new investment capital over the last decade or so has produced a lofty ending valuation, which has yet to mean revert, 12 and which would lead the regression to underestimate the true power of valuation for the low beta factor.

The whole managed futures universe has performed so abysmally that you have to wonder if regression to the mean is about to rescue some of the surviving funds.

«Regression to the mean is the most powerful law in financial physics: Periods of above - average performance are inevitably followed by below - average returns, and bad times inevitably set the stage for surprisingly good performance.»

«Regression to the mean» refers to the inevitability of prices revisiting a long - term trend.

The analysis provides insight into the rate of regression toward the mean and the mean to which results regress.

Regression to the mean is nature's way of leveling the playing field, in almost every game, including investing.

This tendency for trends to flip with the passage of time is called regression to the mean.

The law of averages and regression to the mean, sort of dictate that on a long time line your Big Bad Active Fund will do about as well as the market did.

This phenomenon leads to nonsense when people attribute the regression to the mean to some particular scientific law, rather than to the natural behavior of any random quantity.

Perhaps it's my age (I remember when I had do do linear regressions with a pencil and paper for the sums, and a slide rule to help with the squares and square roots), but a fundamental principle of a linear least squares regression is that the best fit line passes through the point represented by the mean X and mean Y values.

A linear regression says «let's allow our mean Y to depend on X in a linear fashion», instead of using a single mean Y to represent the data (independent of X).

According to the submitted paper, they «fit each record [ENSO and AMO times series] separately to 5th order polynomials using a linear least - squares regression; we subtracted the respective fits... This procedure effectively removes slow changes such as global warming and the ~ 70 year cycle of the AMO, and gives each record zero mean.»

I have linearly extended the ensemble mean model values for the post 2003 period (using a regression from 1993 - 2002) to get a rough sense of where those runs might have gone.

As it is, a forcast for 2005 based on OLS regression for 1988 to 2006 has a mean of 0.61 C with a 95 % CI from 0.37 C to 0.84 C.

Whether linear or curvilinear correlations, and regardless of the regression method, or outlier elimination process for values in a data set + / - 3 s.d.'s from the mean, error analysis and going back to raw data are essential procedures.

Their approach requires an estimate of the forced global mean temperature in a given year (excluding any natural variability), which are derived from Otto et al (2015), who employ a regression approach to reconstruct a prediction of global mean temperatures as a function of anthropogenic and natural forcing agents.

To be explicit, when I said «linear model» I meant the assumption of validity of linear regression between temperature and independent variables.

Anyway, the change from the usual certainty level also means — I'm estimating here — that the coefficient of the regression associated with time is estimated at 0.5 W - 2 with a 95 % chance of being anywhere in the interval -(some - number) to one - point - something Wm - 2.

Then this means that the coefficient of the regression associated with time is estimated at 0.5 W - 2 with a 90 % chance of being anywhere in the interval 0.07 to 0.93 Wm - 2.

All calculations (i.e. here or here) using the regression method - observed GMST vs. the total forcings - come to TCR estimates which are well below the mean of the CMIP5 models of 1.8 K / doubling CO2.

All it actually means is the linear regression model doesn't fit the data perfectly, but of course not, that's to be expected given temperature data doesn't follow a perfect line.

In our revision of the historical runoff model, we attempted to add several parameters of temperature — seasonal means, maximums, and minimums — as explanatory variables to the revised regression model but none were significant.

They draw a line on a graph showing the rate of warming from that unnatural peak in 1998 to now, and make it look like warming has continued at a steady pace, and not accelerated as expected (an argument that would fail any Statistics 101 class, as it ignores «regression to the mean»).

Then we add / subtract this scaled interannual regression map to / from the anthropogenically - forced component of the trend over the next 30 years, the latter estimated from the ensemble - mean of the CESM - LE (Fig. 8) or the ensemble - mean of the 38 CMIP5 models (Fig. 9).