Let $\xi $ and $ \eta$ be independent random variables, $\xi$ is $U[0,1]$ , $\eta$ takes values $1/3$ and $2/3$ with probability $1/2$.
Find the PDF for $\xi + \eta$
It is easy for two continuous random variables, but what should I do in this situation?
PDF for $\xi + \eta$
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Preliminary Lemma: if $f$ is a pdf, $$f(x)*\delta_a(x)=f(x-a).$$
Proof: Let $X$ a random variable with pdf $f$ and $Y=a$ (constant), thus with pdf $\delta_a$, ("a probability peak of value 1 concentrated in position $a$"). Then the pdf of random variable $X+Y=X+a$, which is clearly the shifted version: $x\mapsto f(x-a)$, is besides, the pdf of a sum of random variables, thus the convolution of the associated pdfs.
The pdf of Random Variable $X$ is $\Pi_{[0,1]}$, the characteristic function of interval $[0,1]$.
The pdf of Random Variable $Y$ is $\frac12(\delta_{1/3}+\delta_{2/3})$.
The pdf of $X+Y$ is the convolution:
$$g=\Pi_{[0,1]} * \frac12(\delta_{1/3}+\delta_{2/3})$$
By distributivity property:
$$g=\frac12\Pi_{[0,1]} * \delta_{1/3}+\frac12\Pi_{[0,1]} * \delta_{2/3}$$
Using the Lemma, one can write:
$$g=\frac12\Pi_{[1/3,4/3]}+\frac12\Pi_{[2/3,5/3]}$$
which can be also written:
$$g=\frac12\Pi_{[1/3,2/3]}+\Pi_{[2/3,4/3]}+\frac12\Pi_{[4/3,5/3]}$$
The graphical representation of this pdf is:

Comment: Here is a simulation in R statistical software that may help you verify the answer when you get it. I used $X \sim Unif(0,1)$ and $Y$ taking values $1/3$ and $2/3$ each with probability $1/2,$ and $S = X + Y.$ With a million realizations of each random variable simulated means and SDs should be accurate to about three places.
You can view this as a 50:50 mixture of two uniform distributions, one of them on the interval $(1/3, 4/3).$