Since, A is a 4x5 Matrix
Therefore, it means that A has 4 Linear Equations with 5 variables.
Now, you can write the x in Ax = 0 as:
x = | ![](denied:data:image/png;base64,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) |
This means that x has 2 Linear Independent variables.
This will only happen when A has 2 Free Variables.
It's a fact that,
Total number of Variables = Number of Pivot Variables + Number of Free Variables
5 = Number of Pivot Variables + 2
Number of Pivot Variables (or Rank of A) = 3