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Q. Explain Correlation Coefficient?
Ans.
The strength of a linear correlation is determined by how precisely the y variable shifts as the x variable increases. The two pictures on the right show data with a higher correlation than those on the left.
Data is said to have a perfect correlation if all points lie exactly along a line.
The correlation coefficient, r, is a measure of the strength of the correlation. It is a number between 1 and +1. +1 indicates a perfect positive correlation and 1 indicated a perfect negative correlation. If r is positive, then there is a positive correlation between the two variables. If r is negative, there is a negative correlation between the variables.
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Would there be a possibility to use the correlation coefficient to identify collocations? Compare with the Chi2 test. • How could we maybe do that?
at what p-value do we reject the null hypothesis for the Dublin-Watson test
A manufacturer of VCRs plans to purchase a particular component from suppliers A, B and C. 30% of the components are to be purchased from A, 20% from B and 50% from C. In the past,
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Bond premium cycle The excess of the price for which a connection is acquired or sold over its face value resulting from a disparity connecting the market rate of interest and the
Q. Illustrate Linear Correlation? Ans. In bivariate studies we are often interested in finding out whether there is a relationship between two sets of data. Are SAT score
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