# data[].attributes.definition
The values represent the average over a time interval, such as daily mean discharge or daily mean temperature.

# data[].attributes.definition
The values are categorical rather than continuous valued quantities.

# data[].attributes.definition
The values are categorical rather than continuous valued quantities.

# data[].attributes.definition
In statistics, a confidence interval (CI) is a type of interval estimate of a statistical parameter. It is an observed interval (i.e., it is calculated from the observations), in principle different from sample to sample, that frequently includes the value of an unobservable parameter of interest if the experiment is repeated. How frequently the observed interval contains the parameter is determined by the confidence level or confidence coefficient.

# data[].attributes.definition
In statistics, a confidence interval (CI) is a type of interval estimate of a statistical parameter. It is an observed interval (i.e., it is calculated from the observations), in principle different from sample to sample, that frequently includes the value of an unobservable parameter of interest if the experiment is repeated. How frequently the observed interval contains the parameter is determined by the confidence level or confidence coefficient.

# data[].attributes.definition
The values are quantities that can be interpreted as constant for all time, or over the time interval to a subsequent measurement of the same variable at the same site.

# data[].attributes.definition
The values are quantities that can be interpreted as constant for all time, or over the time interval to a subsequent measurement of the same variable at the same site.

# data[].attributes.definition
A quantity specified at a particular instant in time measured with sufficient frequency (small spacing) to be interpreted as a continuous record of the phenomenon.

# data[].attributes.definition
A quantity specified at a particular instant in time measured with sufficient frequency (small spacing) to be interpreted as a continuous record of the phenomenon.

# data[].attributes.definition
The values represent the cumulative value of a variable measured or calculated up to a given instant of time, such as cumulative volume of flow or cumulative precipitation.

# data[].attributes.definition
The values represent the cumulative value of a variable measured or calculated up to a given instant of time, such as cumulative volume of flow or cumulative precipitation.

# data[].attributes.definition
The values represent the incremental value of a variable over a time interval, such as the incremental volume of flow or incremental precipitation.

# data[].attributes.definition
The values represent the incremental value of a variable over a time interval, such as the incremental volume of flow or incremental precipitation.

# data[].attributes.definition
The values are the maximum values occurring at some time during a time interval, such as annual maximum discharge or a daily maximum air temperature.

# data[].attributes.definition
The values represent the median over a time interval, such as daily median discharge or daily median temperature.

# data[].attributes.definition
The values are the minimum values occurring at some time during a time interval, such as 7-day low flow for a year or the daily minimum temperature.

# data[].attributes.definition
The values are the most frequent values occurring at some time during a time interval, such as annual most frequent wind direction.

# data[].attributes.definition
The values are the most frequent values occurring at some time during a time interval, such as annual most frequent wind direction.

# data[].attributes.definition
The phenomenon is sampled at a particular instant in time but with a frequency that is too coarse for interpreting the record as continuous. This would be the case when the spacing is significantly larger than the support and the time scale of fluctuation of the phenomenon, such as for example infrequent water quality samples.

# data[].attributes.definition
The phenomenon is sampled at a particular instant in time but with a frequency that is too coarse for interpreting the record as continuous. This would be the case when the spacing is significantly larger than the support and the time scale of fluctuation of the phenomenon, such as for example infrequent water quality samples.

# data[].attributes.definition
The values represent the standard deviation of a set of observations made over a time interval. Standard deviation computed using the unbiased formula SQRT(SUM((Xi-mean)^2)/(n-1)) are preferred. The specific formula used to compute variance can be noted in the methods description.

# data[].attributes.definition
The values represent the standard deviation of a set of observations made over a time interval. Standard deviation computed using the unbiased formula SQRT(SUM((Xi-mean)^2)/(n-1)) are preferred. The specific formula used to compute variance can be noted in the methods description.

# data[].attributes.definition
The standard error of the mean (SEM) quantifies the precision of the mean. It is a measure of how far your sample mean is likely to be from the true population mean. It is expressed in the same units as the data.

# data[].attributes.definition
The standard error of the mean (SEM) quantifies the precision of the mean. It is a measure of how far your sample mean is likely to be from the true population mean. It is expressed in the same units as the data.

# data[].attributes.definition
The values represent the variance of a set of observations made over a time interval. Variance computed using the unbiased formula SUM((Xi-mean)^2)/(n-1) are preferred. The specific formula used to compute variance can be noted in the methods description.

# data[].attributes.definition
The values represent the variance of a set of observations made over a time interval. Variance computed using the unbiased formula SUM((Xi-mean)^2)/(n-1) are preferred. The specific formula used to compute variance can be noted in the methods description.