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Python adaptation of Danielle Navarro's Learning Statistics with R (http://learningstatisticswithr.com/). Work in progress!

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Table in section 5.2.3 is the same as the one I 5.1.1 which doesn't seem right. Furthermore, the code for Fig. 5.6 in section doesn't work: matplotlib.pyplot should be imported...

Re-do: 1. Chapter on t-tests 2. Chapter on 1-way anova

Typo ![image](https://github.com/ethanweed/pythonbook/assets/10561061/dd7d381e-95a3-4205-8978-728c33265e62)

It would be very nice to have a full pdf version of this thing, with a proper, complete summary.... for offline reading or even printing. I always use the Danielle...

Screenshot of the part: ![image](https://github.com/ethanweed/pythonbook/assets/10561061/1ae2f649-ccc7-447a-8a18-faae599c10c1) ------------ I believe $\epsilon$ should be replaced with $\epsilon_{ik}$ in the last equation, for clarity.

Correcting variable naming in python code: from statistics import mean X = [56, 31, 56, 8, 32] # 1. enter the data X_bar = mean(X) # 2. find the mean...

Corrected TeX command: AAD\mbox{}(X) = \frac{1}{N} \sum_{i = 1}^N |X_i - \bar{X}|

Corrected grammatical error: There have been a lot of finals in this period so printing afl finalists using print(afl_finalists) will just fill the screen.

Corrected spelling error: Now, as you may remember (you do remember, right?) I spent some time whining back in [the previous chapter about how the Python developers were really mean...