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9 results for “error”

Formulae (9)

SE = \frac{\sigma}{\sqrt{n}}

Standard deviation of the sample mean.

E = z\frac{\sigma}{\sqrt{n}}

Half-width of a confidence interval for the mean.

MSE = \frac{1}{n}\sum_{i=1}^{n}(y_i - \hat{y}_i)^2

Average of squared differences between predicted and actual values.

RMSE = \sqrt{\frac{1}{n}\sum_{i=1}^{n}(y_i - \hat{y}_i)^2}

Square root of MSE, in the same units as the target variable.

MAE = \frac{1}{n}\sum_{i=1}^{n}|y_i - \hat{y}_i|

Average of absolute differences between predictions and actual values.

Error = Bias^2 + Variance + \sigma^2

Total expected error decomposes into bias, variance, and irreducible noise.

p = b_1 \oplus b_2 \oplus \cdots \oplus b_n

XOR of data bits used for error detection.

C = B\log_2(1 + SNR)

Maximum error-free data rate of a noisy channel.

2^r \geq m + r + 1

Parity bits r needed to protect m data bits.