Sentences with phrase «on regression to the mean»

Michael Buchanan should have been betting on regression to the mean; instead, he bet against it.

Not exact matches

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.

You can say it's just regression to the mean, but, even that, Sixers need to do better on defense.

Following a meeting on Tuesday, Rummenigge said that «stagnation means regression» but promised to «find a good and balanced solution».

This means that you will be less likely to see the sleep regression, and in case you have experienced this, you could settle your infant to sleep with hands - on suitable techniques if still swaddled.

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.

This tendency toward mediocrity — sometimes called the Sports Illustrated jinx because an athlete is likely to enter a career lull after appearing on the cover — is a variation on a mathematical principle known as regression to the mean.

I meant to post this outfit on the blog yesterday but we're going through a sleep regression over here that's been taking its toll.

It may be harder to code and analyze essays about paintings than to run another value - added regression on the math and reading scores that the centralized authorities have collected for us, but that doesn't mean it's any less important.

If we used «vehicles» to move gravel from point A to point B... and we calculated an effect size on vehicles... we suffer from «regression towards the mean»; the child's wagon will look more powerful than it is (a higher effect size) and the 5 ton truck will look worse (a lower effect size).

Based on recent information provided by the Accountability Technical Advisory Committee's (TAC) recommendations to ISBE, it is likely that ISBE will move away from linear regression toward Student Growth Percentiles (SGPs) as a means to measure student growth under the new school improvement and accountability system.

Gummy's (Peter Ponzo's) web site Gummy's Tutorial on Mean Regression Reversion to the mean DOES exist.

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

For instance, a reasonable expectation based on forward price - to - earnings data might be a 25 % bearish downturn whenever regression to the mean comes to pass.

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.

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).

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.

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»).

This range is constructed by computing the standard deviation (σ) of the 40 regression values at each grid box for each variable (SLP, SAT and P) based on detrended data during 1920 — 2012, and subtracting / adding these values (multiplied by two) from / to the ensemble mean regression value.

If we have, indeed, only had polar ice for 20 % of the last 6 - million years (from Ian Plimer), then regression - to - the - mean dictates betting on «up» would likely yield better odds at times when we have ice caps to ponder.

«A strong warming and severe drought predicted on the basis of the ensemble mean of the CMIP climate models simulations is supported by our regression analysis only in a very unlikely case of the continually increasing AMO at a rate similar to its 1970 — 2010 increase» 7

The least - squares linear - regression trend on their mean was determined and found equivalent to 0.47 C ° / century.

Either it works or it doesn't but there isn't the tiniest shred of reason to think that it will on the basis of statistics and regression to mean behavior and so on.

The least - squares linear - regression trend on the RSS satellite monthly global mean surface temperature anomaly dataset continues to show no global warming for 18 years 9 months since February 1997, though one - third of all anthropogenic forcings have occurred during the period of the Pause.

An exploratory analysis was to be performed by means of multiple regression with the dependent variable as the sum on the new scale and the independent variables as 14 personality disorder scales defined in DSM - 5, DSM - IV - TR, and DSM - III - R.

A decomposition methodology examined the contribution from different sources in explaining the SES gradient in early cognitive outcomes.34 Similar to the methodology used in the UK Millennium Cohort Study, we focus on the quintile 1 — quintile 5 (Q1 — Q5) and quintile 1 — quintile 3 (Q1 — Q3) gaps and calculate the percentile points and the percentage of the raw gaps explained by each candidate explanatory factor and each domain of factors.2 This was done by taking the product of the mean gap in each explanatory factor (mean difference between Q1 — Q5 and Q1 — Q3) by the β coefficients from linear regression models that predict reading and math ability from SES and all candidate explanatory factors.

According to the procedures posed by Aiken and West (1991), we used the simple slope for the regression of self - esteem on general family function by using the high (one standard deviation above the mean) and low (one standard deviation below the mean) values for social support.