Solution
+In a, the order of operations has been treated poorly, so the answer is incorrect.
+In b, the numbers have been turned into strings, and then divided by `3`. Strings can't be divided by integers, which raises `TypeError`.
+In c, the strings have been turned into numbers, except Python isn't sure how to turn `"12.0"` into an integer due to the decimal place, even though it is followed by `0`. This raises a new, very common error: `ValueError`.
+A simple solution would be:
+
+
+
+a = 12.0
+b = 5.1
+c = 8.5
+mean = (a + b + c) / 3
+print(mean)
+
+
+
+
+## Non-standard mathematical operators
+Python has more specialised mathematical operators stored in external pre-written pieces of code called *libraries*. For example, the `math` library contains more common mathematical tools, like the square root function `sqrt()`.
+
+To use a function from a library, we must first *import* it to our program:
+
+```Python
+import math
+
+print(math.sqrt(16))
+```
+
+Functions from the `math` library can be accessed by preceding them with `math.`. We can also bypass this by importing only the function we need, with this syntax:
+
+```Python
+from math import sqrt
+
+print(sqrt(16))
+```
+
+Finally, some library names are abbreviated by convention (and to save on typing). This is the case for the `numpy` library, which also has a `sqrt` function:
+
+```Python
+import numpy as np
+print(np.sqrt(16))
+```
+
+## Seeking programming help online
+External libraries allow us to complete complex operations by writing few lines of code. In exchange, we need to learn how a library works based on its documentation which can take time. For example, [here is the documentation page](https://numpy.org/doc/stable/reference/generated/numpy.sqrt.html) for `numpy.sqrt`. There is also authoritative documentation for standard Python, like [this section on numeric types](https://docs.python.org/3/library/stdtypes.html#numeric-types-int-float-complex).
+
+This kind of documentation is extremely reliable, since it's written by the authors of the library itself. However, it's so comprehensive that it can be hard to understand. Another good source for programming answers is [Stack Overflow](http://stackoverflow.com), which pops near the top of many internet searches. Take [this page](https://stackoverflow.com/questions/70793490/how-do-i-calculate-square-root-in-python), for example. The top section is a question. Below are answers written by the community and ordered by vote ranking. This means that, even though not every answer is correct, we can dose our trust based on the popularity of the answer, and we can trace back its author.
+
+You may also consider using an AI chatbot to answer your questions. If you do so, you will find that answers to programming questions look extremely similar to the style popularised by Stack Overflow and other such forums for the past few decades. Indeed, Stack Overflow is an influential part of the training set for these chatbots. You might save a bit of time by skipping the online search. In exchange you won't know the provenance of your answer, and therefore won't know how much to trust it. As a general guide, if an answer is hard to find by a standard search engine, a chatbot's answers are more likely to be wrong and made up.
+
+Whatever the source, always check that you understand the code you find before re-using it, and verify the truth of any claims by running some tests on your own computer.
+
+```{admonition} Task
+Using a search engine, find a function to operate a Least Squares Fit on a series of data. Get the documentation for the function and a Stack Overflow page explaining its use.
+```
+
+