Examples of using Correlation coefficient in English and their translations into German
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Xn The correlation coefficient is obviously 1.
Analyses of the data showed a correlation coefficient of 89.
Spearman Correlation Coefficient(rs) between VA and CS was rs =0.60.
Explanation of the key values The r value is called the correlation coefficient.
How to calculate the correlation coefficient between two variables in Excel?
Correlation coefficient(r) 0.89 Regression coefficient(b) 0.71 Ordinates at the origin(a) 6.6.
The CORREL() function calculates the correlation coefficient of two cell ranges.
The pair correlation coefficient can be used as the simplest indicator.
Explore how individual data points affect the correlation coefficient and best-fit line.
On the other hand, a correlation coefficient of -1 indicates a perfect negative correlation. .
Regional rankings according to total patents andhigh tech patents are similar, confirmed by a correlation coefficient of 0.86.
Although connections seem to be clearer- the correlation coefficient is close to 0.5, clear statements cannot be made here either.
The correlation coefficient for the parameter volume were: 0,07; 0,23; -0,27 and the correlation coefficient for the parameter flow were 0,14; 0,26; and -0,13.
The low t test valuesin(8) and(9) result from both the low degree of certainty and the high intercorrelation simple correlation coefficient between income and the price of pork.
Of each v„ equals 1 while the correlation coefficient of the z,, for each i equals 0.97, hence a negative number.
The correlation coefficient, denoted as r, is the measure of linear correlation(the relationship, in terms of both strength and direction) between two variables.
Some technicians are warning of a potential head andshoulders bearish reversal pattern on US 10Y Yields, which with the correlation coefficient of USD/JPY over the last 20-days at +0.70 should hold USD/JPY traders attention.
It will be recalled that a correlation coefficient of 0.65 means that only 42% of the variance of one of the factors is explained by the other.
The relationship between net migration and the difference between regional andnational rates of unemployment can be measured statistically by the correlation coefficient, which will be nearer to 1, the closer the relationship is see Table 1, which summarises the main features of the relationship.
We usually use correlation coefficient(a value between -1 and 1) to display how strongly two variables are related to each other.
When the index for output prices inthe United States preceded by one quarter the EU-25's index, the correlation coefficient between both series reached 0.99: as for the production index this suggests a small lead for the United States relative to the EU-25.
Note: A correlation coefficient of +1 indicates a perfect positive correlation, which means that as variable X increases, variable Y increases and while variable X decreases, variable Y decreases.
The PEARSON() function calculates the correlation coefficient of two cell ranges. It is the same as the CORREL function.
The correlation coefficient between the EU-25 and the United States indices was already quite high(0.94) without any lead or lag, but it was slightly higher when using pairs of data shifted by between 2 and 7 quarters ahead for the United States: this indicates that similar movements to those seen in one quarter in the production index in the United States are seen a few quarters later in the production index for the EU-25.
The average change per period, the correlation coefficient as well as an indication if the trend is statistically significant.
The correlation coefficient is considered to be statistically significant if the computed t value is greater than the critical value of a t-distribution with a level of significance of a/2 and n-2 degrees of freedom.
Correlation' in this context means the correlation coefficient between daily returns on the CIU and the index or basket of equities or debt securities it tracks.
We can see that the correlation coefficient and the Fisher value are very high, indicating a close relationship between prevalence(of disability) and age.
Without a lead or lag the correlation coefficient between EU-25 and Japanese indices was very close to 0 over the time period observed, and the coefficient remained very weak when comparing quarterly indices shifted by 1 to 12 quarters in either direction.