Consider the following statements:
1 Both variance and standard deviaiton are measures of variability in the population.
2. Standard deviation is the square of the variance.
Which of the above statements is/are correct?

Options

A. 1 only
B. 2 only
C. Both 1 and 2
D. Neither 1 nor 2

Explanation

To analyze the statements provided in the question, we will evaluate each statement one by one.

### Step 1: Evaluate the first statement
The first statement claims that "Both variance and standard deviation are measures of variability in the population."

- **Variance** is defined as the average of the squared differences from the mean. It quantifies how much the values in a dataset differ from the mean.
- **Standard deviation** is the square root of the variance. It also measures the amount of variation or dispersion in a set of values.

Since both variance and standard deviation are indeed measures of variability, the first statement is **true**.

### Step 2: Evaluate the second statement
The second statement claims that "Standard deviation is the square of the variance."

- As mentioned earlier, standard deviation is not the square of the variance; rather, it is the square root of the variance.

Thus, the second statement is **false**.

### Conclusion
Based on the evaluations:
- The first statement is **true**.
- The second statement is **false**.

Therefore, the correct answer is that only the first statement is correct.

### Final Answer
Only the first statement is correct.

---