A box and whisker plot (box plot) provides a visual representation of the distribution of a dataset, showing the median, quartiles, and potential outliers. While you cannot directly calculate the mean and standard deviation from a box plot, you can make some general observations about the data distribution.

You can get approximate values for the mean and sd, but not their precise values without the raw data (which you can sometimes infer).

In a roughly symmetrical box plot, the mean will approximately equal the median, which is shown as the line in the middle of the box. In a non-symmetrical plot, the mean will be offset from the median in the direction of the longer whisker or the most extreme outliers.

Absent outliers, the sd will typically be approximately one-fourth of the range. If there are a few outliers in either direction, or both directions, one-sixth of the range will usually be a better approximation.

In your examples, it appears that a dot for each individual observation has been overlaid upon the box plot. If so, you could infer a raw data set by reading the score for each obeservation from the indicated scale of the plot, and then you can calculate the mean and sd yourself from that data set. Reading the scores would be subject to some error, of course, but such errors are likely to be approximately random (some a bit high, some a bit low), so the calculated mean and sd should be quite close to the actual values.