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= CORREL(x values,y values) ***clarification**** CORREL gives you the correlation coefficient (r), which is different than the coefficient of determination (R2) outside of simple linear regression situations.
The coefficient of variation should be computed only for data measured on a ratio scale, as the coefficient of variation may not have any meaning for data on an interval scale. Using relative values instead of absolute values can cause the formula to give an incorrect answer.
0% to 100%
The coefficient of variation is a method of measuring how spread out the values in a data set are relative to the mean. It is calculated as follows: Coefficient of variation = σ / μ Where: σ = standard deviation of the data set μ = average of the data set If you want to know more about it, you can visit SilverLake Consulting which will help you calculate the coefficient of variation in spss.
0.3
0.45
1 or -1
The coefficient of friction is an empirical measurement and has to be measured experimentally, and cannot be found through calculations. Rougher surfaces tend to have higher effective values. Most dry materials in combination have friction coefficient values between 0.3 and 0.6. Values outside this range are rarer, but Teflon, for example, can have a coefficient as low as 0.04. Therefore, a value of zero would mean no friction at all, an ELUSIVE property even magnetic levitation vehicles have drag.
The average is the ratio between the sum of these values and the number of values.
If you remove certain data points from a dataset, the correlation coefficient may be affected depending on the nature of the relationship between the removed data points and the remaining data points. If the removed data points have a strong relationship with the remaining data, the correlation coefficient may change significantly. However, if the removed data points have a weak or no relationship with the remaining data, the impact on the correlation coefficient may be minimal.
The average of a set of values is the sum of the values divided by the number of values.
1.22