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In R-squared coefficient is the determination of a statistical tool, which measures the level of safety of any operation, which may be due to the performance of a particular benchmark indicator.
Summer Cruisin' Vol. 6
For You: LGCY Selects 004 (Electronic & R&B Mix)
R-Squared Indicator Says Market Could Get Scary
R-Squared Indicator Says Market Could Get Scary
Wells Capital’s James Paulsen has been bullish — correctly — throughout much of the bull market that began in March 2009. But now, Paulsen says that a key sentiment indicator that has predicted many former declines is flashing a warning signal.
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How well this equation describes the data (the 'fit'), is expressed as a correlation coefficient, R2 (R-squared). The closer R2 is to 1.00, the better the fit.
Interpreting R-squared
Once you run a regression, one of the first bits of output is an R-squared. No matter how complicated your regression model, you will almost always interpret the R2.
That's because the R2 tells you a really important piece of information: How much of the variance (the individual differences) in your outcome variable are being explained by your predictors.
Even if you have a statistically significant predictor (a slope that's significantly different from zero), you might still only be explaining a very small proportion of the variance in your outcome.
R2 can be interpreted like this: If R2 = .31, that means that 31% of the variance in your outcome has been explained by your predictor(s).