Step 1: Recall the relation between standard deviation and variance.
We know that:
\[
\text{Variance}=(\text{Standard Deviation})^2
\]
Since the standard deviation of the original six numbers is \(4\), their variance is:
\[
4^2=16
\]
Step 2: Write the transformation of the variables.
Each new number is of the form:
\[
y_i=2x_i+3
\]
So the new set is obtained by multiplying each original observation by \(2\) and then adding \(3\).
Step 3: Recall how variance changes under linear transformation.
If
\[
y=ax+b,
\]
then the variance changes as:
\[
\operatorname{Var}(y)=a^2\operatorname{Var}(x)
\]
The constant term \(b\) does not affect the variance.
Step 4: Identify the values of \(a\) and \(b\).
Here,
\[
a=2 \quad \text{and} \quad b=3
\]
Therefore:
\[
\operatorname{Var}(2x+3)=2^2\operatorname{Var}(x)
\]
Step 5: Substitute the original variance.
Since the original variance is \(16\), we get:
\[
\operatorname{Var}(2x+3)=4\times 16
\]
Step 6: Simplify.
\[
4\times 16=64
\]
Step 7: State the final answer.
Hence, the variance of \(2x_1+3,2x_2+3,2x_3+3,2x_4+3,2x_5+3,2x_6+3\) is:
\[
\boxed{64}
\]
which matches option \((1)\).