first-order correlation Antonyms
No Synonyms and anytonyms found
Meaning of first-order correlation
first-order correlation (n)
a partial correlation in which the effects of only one variable are removed (held constant)
first-order correlation Sentence Examples
- In statistics, first-order correlation measures the degree of linear association between two variables.
- The first-order correlation coefficient ranges between -1 and 1, where -1 indicates a perfect negative correlation, 0 indicates no correlation, and 1 indicates a perfect positive correlation.
- A positive first-order correlation coefficient indicates that as one variable increases, the other variable tends to increase as well, while a negative first-order correlation coefficient indicates that as one variable increases, the other variable tends to decrease.
- The strength of the first-order correlation is determined by the magnitude of the correlation coefficient.
- A first-order correlation coefficient of 0.5 indicates a moderate positive correlation, while a first-order correlation coefficient of -0.3 indicates a moderate negative correlation.
- The first-order correlation coefficient is a useful tool for understanding the relationship between two variables, but it is important to note that it does not imply causation.
- In time series analysis, the first-order correlation coefficient is used to measure the autocorrelation of a series.
- Autocorrelation is the correlation between a series and its own lagged values.
- A positive autocorrelation coefficient indicates that the series is positively correlated with its own past values, while a negative autocorrelation coefficient indicates that the series is negatively correlated with its own past values.
- The first-order correlation coefficient is a simple but powerful tool for understanding the relationship between two variables.
FAQs About the word first-order correlation
a partial correlation in which the effects of only one variable are removed (held constant)
No synonyms found.
No antonyms found.
In statistics, first-order correlation measures the degree of linear association between two variables.
The first-order correlation coefficient ranges between -1 and 1, where -1 indicates a perfect negative correlation, 0 indicates no correlation, and 1 indicates a perfect positive correlation.
A positive first-order correlation coefficient indicates that as one variable increases, the other variable tends to increase as well, while a negative first-order correlation coefficient indicates that as one variable increases, the other variable tends to decrease.
The strength of the first-order correlation is determined by the magnitude of the correlation coefficient.
