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An age-standardised rate (ASR) is a summary measure of the rate that a population would have if it had a standard age structure. Standardization is necessary when comparing several populations that differ with respect to age because age has a powerful influence on the risk of dying from cancer.
Typically, to standardize variables, you calculate the mean and standard deviation for a variable. Then, for each observed value of the variable, you subtract the mean and divide by the standard deviation.
Subtract the mean,, from the value you want to convert, X. Divide the result from Step 1 by the standard deviation,.
Subtract the mean,, from the value you want to convert, X. Divide the result from Step 1 by the standard deviation,.
From a business standpoint, standardization refers to the practice of maintaining some level of consistency in the product or service that a company provides. A company wants to produce a consistent product, so consumers will know what they're buying. Say, for instance, a bakery produces loaves of wheat bread.
The benefits of standardization. Fundamentally, standardization means that your employees have an established, time-tested process to use. When done well, standardization can decrease ambiguity and guesswork, guarantee quality, boost productivity, and increase employee morale.
When you standardize a random variable, its mean becomes zero and its standard deviation becomes one. Therefore, if the Z score of x is zero, then the value of x is equal to the mean. If the Z score of x is one, then the value of x is one standard deviation above the mean.
A z-score, or standard score, is used for standardizing scores on the same scale by dividing a score's deviation by the standard deviation in a data set. The result is a standard score. It measures the number of standard deviations that a given data point is from the mean.
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