To calculate the covariance $\text{Cov}(1X, 6Y)$, we can use the following property of covariance:

$\text{Cov}(aX, bY) = ab \cdot \text{Cov}(X, Y)$

Where $a$ and $b$ are constants.

In this case, $a = 1$ and $b = 6$. Thus,

$\text{Cov}(1X, 6Y) = 1 \times 6 \times \text{Cov}(X, Y) = 6 \times 4.4 = 26.4$

So, $\text{Cov}(1X, 6Y) = 26.4$.

Would you like more details on covariance or any other related topic?

Here are some related questions:

1. What are other properties of covariance?
2. How does covariance relate to correlation?
3. What is the interpretation of positive and negative covariance?
4. How can covariance be used in portfolio risk management?
5. How does covariance apply to multiple variables?

Tip: Covariance measures the direction of a linear relationship between two variables but doesn't standardize their scales—correlation helps with that.