One fairly straightforward way is to compute the fraction of likes as
$$
\text{fraction}_\text{likes} = \frac{\text{number}_\text{likes}}
{\text{number}_\text{likes}+
\text{number}_\text{dislikes}}
$$
and then if $\text{fraction}_\text{likes}$ is below $0.2$, that's one star; if it's at least $0.2$ but less than $0.4$, it's two stars; and so on. More than $0.8$ is five stars.
ETA: If you allow for zero stars, you could break it down as follows: less than $0.1$, zero stars; at least $0.1$ but less than $0.3$, one star; and so on. More than $0.9$ is five stars.
Suppose there are $n$ products.
For each product, there is a minimum price $p_i$ and a maximum price $q_i$ and the number of that product $f_i$.
Then the mean price of all products lies between a lower bound $\bar p$ and an upper bound $\bar q$, where
$$\bar p=\frac{\Sigma p_if_i}{\Sigma f_i}$$
and $$\bar q=\frac{\Sigma q_if_i}{\Sigma f_i}$$
You have:
$f_1=100$, $p_1=0$, $q_1=10$.
$f_2=150$, $p_2=10$, $q_2=20$.
$f_3=80$, $p_3=20$, $q_3=30$.
$$\bar p=\frac{0 \times 100+ 10 \times 150 + 20 \times 80}{100+150+80}=\frac{3100}{330} \approx 9.39$$
$$\bar q=\frac{10 \times 100+ 20 \times 150 + 30 \times 80}{100+150+80}=\frac{6400}{330} \approx 19.39$$
Best Answer
In most rating systems, the final score is the average of all the ratings, so in your example, I would assume that the average rating is $9.2/10$.
It is possible that a rating system uses a different measure of central tendency. If you can identify the measure of central tendency that is being used and you have enough information, it may be possible to calculate or estimate the average rating.
Sometimes, we use even more complicated rating systems, like the Elo rating system that predicts the outcome of chess matches, but I doubt foursquare is using anything like that.