Calculating the Coefficient of Concurrent Deviations

To calculate the coefficient of concurrent deviations, we need to know the number of concurrent deviations and the number of pairs of observations. In this question, we are given that the number of concurrent deviations is 4 for 10 pairs of observations. Let's calculate the coefficient of concurrent deviations step by step.

Step 1: Define the Terms

Before proceeding with the calculation, let's define the terms involved in the coefficient of concurrent deviations:

- Concurrent Deviations: The number of times two variables deviate in the same direction.
- Coefficient of Concurrent Deviations: It is calculated by dividing the number of concurrent deviations by the number of pairs of observations.

Step 2: Calculate the Coefficient of Concurrent Deviations

In this question, we are given that the number of concurrent deviations is 4 for 10 pairs of observations. So, we can calculate the coefficient of concurrent deviations using the formula:

Coefficient of Concurrent Deviations = Number of Concurrent Deviations / Number of Pairs of Observations

Plugging in the given values:

Coefficient of Concurrent Deviations = 4 / 10

Simplifying the expression:

Coefficient of Concurrent Deviations = 0.4

Step 3: Interpret the Result

The coefficient of concurrent deviations indicates the degree of similarity or agreement between two variables. In this case, the coefficient is 0.4, which means that there is a moderate level of agreement between the two variables.

- A coefficient of 0 indicates no agreement.
- A coefficient of 1 indicates perfect agreement.
- A coefficient between 0 and 1 indicates varying levels of agreement, with higher values indicating stronger agreement.

In this case, the coefficient of 0.4 suggests that there is some agreement between the two variables, but it is not very strong.

Conclusion

The coefficient of concurrent deviations is calculated by dividing the number of concurrent deviations by the number of pairs of observations. In this question, we found that the coefficient is 0.4, indicating a moderate level of agreement between the two variables.