Why does Randomized Quicksort have O(n log n) worst-case runtime cost Randomized Quick Sort is an extension of Quick Sort in which the pivot element is chosen randomly. What can be the worst case time complexity of this algorithm. According to me, it should be $O(n^2)$, as the worst case happens when randomly chosen pivot is selected in sorted or reverse sorted order. But in some texts [1] [2] its worst case time complexity is written as $O(n\log{n})$

What's correct?
Both of your sources refer to the "worst-case expected running time" of $O(n \log n).$ I'm guessing this refers to the expected time requirement, which differs from the absolute worst case.

Quicksort usually has an absolute worst-case time requirement of $O(n^2)$. The worst case occurs when, at every step, the partition procedure splits an $n$-length array into arrays of size $1$ and $n-1$. This "unlucky" selection of pivot elements requires $O(n)$ recursive calls, leading to a $O(n^2)$ worst-case.

Choosing the pivot randomly or randomly shuffling the array prior to sorting has the effect of rendering the worst-case very unlikely, particularly for large arrays. See Wikipedia for a proof that the expected time requirement is $O(n\log n)$. According to another source, "the probability that quicksort will use a quadratic number of compares when sorting a large array on your computer is much less than the probability that your computer will be struck by lightning."

Edit:

Per Bangye's comment, you can eliminate the worst-case pivot selection sequence by always selecting the median element as the pivot. Since finding the median takes $O(n)$ time, this gives $\Theta(n \log n)$ worst-case performance. However, since randomized quicksort is very unlikely to stumble upon the worst case, the deterministic median-finding variant of quicksort is rarely used.