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To standardize a dataset using the Z-score formula, first compute the mean ($\mu$) and standard deviation ($\sigma$) of the dataset. Then, for each original data value $X$, apply the formula $X' = \frac{X - \mu}{\sigma}$ to convert it into a standardized score.

Conditions: Requires knowing the mean and standard deviation of the dataset

To standardize a dataset using the Z-score formula, first compute the mean ($\mu$) and standard deviation ($\sigma$) of the dataset. Then, for each original data value $X$, apply the formula $X' = \frac{X - \mu}{\sigma}$ to convert it into a standardized score.

Conditions: Requires knowing the mean and standard deviation of the dataset

Standard deviation is calculated by finding the squared differences from the mean, averaging those squared differences to get the variance, and then taking the square root of the variance. The formula is $\sigma = \sqrt{\frac{\sum (X - \mu)^2}{N}}$.

Conditions: The mean $\mu$ of the dataset has already been calculated.

Standard deviation is calculated by finding the squared differences from the mean, averaging those squared differences to get the variance, and then taking the square root of the variance. The formula is $\sigma = \sqrt{\frac{\sum (X - \mu)^2}{N}}$.

Conditions: The mean $\mu$ of the dataset has already been calculated.