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For example, to make 100 mL of 50% alc/vol ethanol solution, water would be added to 50 mL of ethanol to make up exactly 100 mL. Whereas to make a 50% v/v ethanol solution, 50 mL of ethanol and 50 mL of water could be mixed but the resulting volume of solution will measure less than 100 mL due to the change of volume on mixing, and will contain ...
The mean global content of water vapor in the atmosphere is roughly sufficient to cover the surface of the planet with a layer of liquid water about 25 mm deep. [ 40 ] [ 41 ] [ 42 ] The mean annual precipitation for the planet is about 1 metre, a comparison which implies a rapid turnover of water in the air – on average, the residence time of ...
Smoothing of a noisy sine (blue curve) with a moving average (red curve). In statistics, a moving average (rolling average or running average or moving mean [1] or rolling mean) is a calculation to analyze data points by creating a series of averages of different selections of the full data set.
This forms a distribution of different means, and this distribution has its own mean and variance. Mathematically, the variance of the sampling mean distribution obtained is equal to the variance of the population divided by the sample size. This is because as the sample size increases, sample means cluster more closely around the population mean.
Pearson's correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. The form of the definition involves a "product moment", that is, the mean (the first moment about the origin) of the product of the mean-adjusted random variables; hence the modifier product-moment in the name.
Mount Everest, Earth's highest mountain. A mountain is an elevated portion of the Earth's crust, generally with steep sides that show significant exposed bedrock.Although definitions vary, a mountain may differ from a plateau in having a limited summit area, and is usually higher than a hill, typically rising at least 300 metres (980 ft) above the surrounding land.
The size of this difference is likely to be large especially when the size of the training data set is small, or when the number of parameters in the model is large. Cross-validation is a way to estimate the size of this effect.
One technique is to fix sample size so that there is a 50% chance of detecting a process shift of a given amount (for example, from 1% defective to 5% defective). If δ is the size of the shift to detect, then the sample size should be set to n ≥ ( 3 δ ) 2 p ¯ ( 1 − p ¯ ) {\displaystyle n\geq \left({\frac {3}{\delta }}\right)^{2}{\bar {p ...