A probability density function must be nonnegative and have definite integral one. Here
Therefore
This value is positive, so the nonnegativity requirement also holds.
The cosine function is positive on and negative on . Thus any nonzero makes negative on an interval of positive length. Taking makes the total definite integral zero. Hence
Normalization alone would suggest , but that candidate still violates nonnegativity and therefore is not a probability density function.
We need . Indeed, if , the function is negative on ; if , the improper integral diverges at zero; and if , its support interval is empty. For ,
Setting this equal to one gives the unique admissible value
On this interval , so both requirements for a probability density function are met.

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