If `r(X, Y)=r`, then `r(aX,bY)` is also equal to r.

Answer

To determine whether the statement "If \( r(X, Y) = r \), then \( r(aX, bY) \) is also equal to \( r \)" is true or false, we will analyze the correlation coefficient and its properties.

### Step-by-Step Solution:

1. **Understanding the Correlation Coefficient**:
The correlation coefficient \( r(X, Y) \) is defined as:
\[ r(X, Y) = \frac{\text{Cov}(X, Y)}{\sqrt{\text{Var}(X) \cdot \text{Var}(Y)}} \]
where \( \text{Cov}(X, Y) \) is the covariance between \( X \) and \( Y \), and \( \text{Var}(X) \) and \( \text{Var}(Y) \) are the variances of \( X \) and \( Y \) respectively.

2. **Finding the Correlation for Scaled Variables**:
We need to find \( r(aX, bY) \):
\[ r(aX, bY) = \frac{\text{Cov}(aX, bY)}{\sqrt{\text{Var}(aX) \cdot \text{Var}(bY)}} \]

3. **Calculating Covariance**:
The covariance of \( aX \) and \( bY \) can be expressed as:
\[ \text{Cov}(aX, bY) = ab \cdot \text{Cov}(X, Y) \]

4. **Calculating Variance**:
The variances of \( aX \) and \( bY \) are:
\[ \text{Var}(aX) = a^2 \cdot \text{Var}(X) \]
\[ \text{Var}(bY) = b^2 \cdot \text{Var}(Y) \]

5. **Substituting into the Correlation Formula**:
Now substituting these into the correlation formula:
\[ r(aX, bY) = \frac{ab \cdot \text{Cov}(X, Y)}{\sqrt{(a^2 \cdot \text{Var}(X)) \cdot (b^2 \cdot \text{Var}(Y))}} \]
Simplifying this gives:
\[ r(aX, bY) = \frac{ab \cdot \text{Cov}(X, Y)}{ab \sqrt{\text{Var}(X) \cdot \text{Var}(Y)}} \]
\[ r(aX, bY) = \frac{\text{Cov}(X, Y)}{\sqrt{\text{Var}(X) \cdot \text{Var}(Y)}} \]

6. **Conclusion**:
Thus, we find that:
\[ r(aX, bY) = r(X, Y) \]
Therefore, if \( r(X, Y) = r \), then \( r(aX, bY) = r \) as well.

### Final Answer:
The statement is **True**.