[meric]

>> A prediction is therefore the use of observations of A to predict B, to show a cause-effect relationship. I see the disappearance of the middle class (A), and on that basis I predict the fall of civilization (B). I see gathering clouds (A), and on that basis I predict rain (B) -- and puddles (C).

You are using the temporal sense of the word "predict", not the cross-sectional sense. Just because you can use the word predict when there is a cause-effect relationship doesn't mean you can't if there isn't. Here is an example illustrating this: I see lots of graffiti in the town (A) and on that basis, predict this town has a high crime rate (B). Notice this prediction was made independent of time.

>> A prediction forges a link between an observation (A) and an outcome (B). It assumes a cause-effect relationship, one that may not be real, but a word isn't responsible for how people misuse it.

A prediction forges a link between an observation (A) and an outcome (B) to explain a correlation relationship, which may or may not be because of a cause-effect relationship.

>> Yes -- an observation of a small sample (A) is used as the basis for a prediction about the population as a whole (B). Also, remember that "prediction" commonly refers to an assertion about the future (B) based on present observations (A).

Let's say I am a statistician and after surveying 10% of the population, found out lower income earners are correlated with a lower IQ. I use this observation as a basis for a prediction about the population as a whole - that lower income earners can predict a lower IQ. Notice again, time is irrelevant.

>> Also, remember that "prediction" commonly refers to an assertion about the future (B) based on present observations (A).

A word may have more than one sense. I am talking about the word prediction as used in statistics.

>> The marijuana use, and the IQ drop, are only correlated -- one does not predict the other.

If they are correlated then you can use the evidence in the sample to make general predictions in the population (independent of time), provided your experiment methodology was valid.

[lutusp]

> You are using the temporal sense of the word "predict" ...

Yes -- that's because that's how the word is defined.

http://en.wikipedia.org/wiki/Prediction

"A prediction (Latin præ-, "before," and dicere, "to say") or forecast is a statement about the way things will happen in the future, often but not always based on experience or knowledge." (Emphasis added.)

> A word may have more than one sense. I am talking about the word prediction as used in statistics.

Yes, all right. Statistics uses the word in the same way, for the same purpose -- as a description of a forecasting method, a statement about the future based on past and present data. Consider the various regression-based prediction methods that are, by definition, statements about the future, based on the past.

http://www.isixsigma.com/tools-templates/risk-management/use...

"Forecasting is a business and communicative process and not merely a statistical tool. Basic forecasting methods serve to predict future events and conditions and should be key decision-making elements for management in service organizations."

Shall I list ten more references that make the same point about statistical prediction? How about just one:

http://en.wikipedia.org/wiki/Regression_analysis

"Regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning."

> If they are correlated then you can use the evidence in the sample to make general predictions in the population ...

Only if you don't understand science. Correlation is not causation.

[meric]

Prediction and forecasting are two different things in regression.

Regression is for predicting a dependent variable based one or more independent variables. It may or may not involve a time component.

"Regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning."

Exactly. Prediction and forecasting are not the same thing. That's why they had to state both.

I know your bio is impressive, but I've studied statistics for two years, specifically time-series forecasting and regression modelling. Predictions are a lot of the times not made in a temporal context. E.g. if you predict aspects of the population based on your observations in a sample.

>> Only if you don't understand science. Correlation is not causation.

I might not understand science as well as you do, but I have some modicum of ability in statistics, so there's no need to wave "Correlation is not causation." at me in every reply you make.

Prediction are not always made as a result of a causation.

[lutusp]

> Prediction and forecasting are two different things in regression.

"Prediction" and "forecasting" are synonymous, in both common usage and in statistics.

> Prediction and forecasting are not the same thing. That's why they had to state both.

No they said both so people who refuse to accept the fact that they're synonymous, won't feel left out in the cold.

http://en.wikipedia.org/wiki/Prediction : "A prediction (Latin præ-, "before," and dicere, "to say") or forecast is ..."

http://en.wikipedia.org/wiki/Forecasting : "Forecasting is the process of making statements about events whose actual outcomes (typically) have not yet been observed. A commonplace example might be estimation of some variable of interest at some specified future date. Prediction is a similar, but more general term."

http://dictionary.reference.com/browse/prediction: "Synonyms: forecast, augury, prognostication, divination, projection."

http://dictionary.reference.com/browse/forecast: "Synonyms: 1. foretell, anticipate. See predict. 3. project. 4, 7. guess, estimate. 9. forethought, prescience."

How can you go on like this about a word that literally means "to say before"?

> Predictions are a lot of the times not made in a temporal context ...

Yes, but those also represent the use of a set of observations (A) to assert a cause-effect relationship with some B. You objected that "prediction" wasn't about time, but it is. You also objected that prediction wasn't about arguing a cause-effect relationship, but it is.

> Prediction are not always made as a result of a causation.

Yes, and "literally" doesn't always mean literally -- sometimes it means "figuratively.":

http://dictionary.reference.com/browse/literally:

"1. in the literal or strict sense: What does the word mean literally?

4. in effect; in substance; very nearly; virtually."

The above is my favorite example of the perversity of arguing about word meanings, as though a word that usually means something, can be said to always mean that.

> I know your bio is impressive ...

Oh, please, let's not go there, all right? Nothing is more certain to undermine an argument than an appeal to authority -- either positive of negative (an in "I'm not an authority, but ..."). Science rejects authority -- the largest amount of eminence is trumped by the smallest amount of evidence.

[meric]

"In statistics, prediction is a part of statistical inference. One particular approach to such inference is known as predictive inference, but the prediction can be undertaken within any of the several approaches to statistical inference. Indeed, one description of statistics is that it provides a means of transferring knowledge about a sample of a population to the whole population, and to other related populations, which is not the same as prediction over time. When information is transferred across time, often to specific points in time, the process is known as forecasting."

http://en.wikipedia.org/wiki/Prediction#Statistics

It's not forecasting if it doesn't involve time, but it is if it does. That's why you can find evidence saying "Prediction == Forecasting" because that is true if there is a time component.