The errata list is a list of errors and their corrections that were found after the product was released.
The following errata were submitted by our customers and have not yet been approved or disproved by the author or editor. They solely represent the opinion of the customer.
Color Key: Serious technical mistake Minor technical mistake Language or formatting error Typo Question Note Update
| Version |
Location |
Description |
Submitted by |
Date submitted |
| Printed |
Page pp 80-81
pp. 80-81 |
In Chapter 6 pp 80-81, There is no Exercise 6-1. The first Exercise is labeled 6-2.
In Exercise 6-2, the question refers to Bayes' as Bayes's which the AP style
guide says is not the correct way to indicate possession for a name ending in s. This occurs throughout the text. More a matter of style.
In Exercise 6-2, a likelihood ratio is provided with a value of 1.25 and the author quotes the source. Its derivation is not shown in the book, but a likelihood ratio of 1.19, rather than 1.25, is derived using the author's own methods on his blog.
My work is shown on my github link to my jupyter notebook:
github.com/betsybetsybetsy2021/PythonStatisticsEssentials/blob/main/OReilly_Bayes_Ch6%20(1).ipynb
|
Elizabeth Ellis |
Aug 24, 2023 |
| Printed |
Page pp152, Chapter 11: comparison
The Update |
the normalize function returns 'prob_data' which is the joint.to_numpy().sum() instead of 'joint' which is the normalized joint distribution
is:
def normalize(joint):
"""Normalize a joint distribution."""
prob_data = joint.to_numpy().sum()
joint /= prob_data
return prob_data
should be:
def normalize(joint):
"""Normalize a joint distribution."""
prob_data = joint.to_numpy().sum()
joint /= prob_data
return joint
|
Nolan Meyer |
Apr 07, 2024 |
| Printed |
Page 13
1st paragraph |
Hi professor Downey.
I found a error in 1st paragraph, page 13, Chapter 1 : Probability.
Here we're learning about "The Law of Total Probability" and using the example of the probability of a moderate banker first we calculated using Theorem 2 but when we want to used the "The Law of Total Probability" exists an error there.
The probability, as we can see, is 0.005822... but the probability using The Law is 0.01476..., there are not equal.
First, if we define A = Banker & Moderate
Then
P(Banker & Moderate) = \sum_i P(B_i) \cdot P(Banker & Moderate | B_i),
here we're using B_i as iterative variable like the code, obviously is not formal way to write this but is enough to understand the idea.
Therefore the code is fixed in this way, only adding the conditional Moderate.
sum( prob( (B == i) ) * conditional( proposition = banker & (B == 4) , given = (B == i) ) for i in range (1,8) )
|
Joaquín Desiderio López de la Cruz |
Jun 07, 2023 |