**Page 29:**

The line:

So, using our die roll and coin toss example, the probability of rolling a number less than 6 or flipping a heads is:

Should now read:

So, using our die roll and coin toss example, the probability of rolling a number equal to 6 or flipping a heads is:

**Page 41:**

The y axis on Figure 4.2:

B(k; 10, 1/2)

Should now read:

B(k; 10, 1/6)

And the caption for Figure 4.2:

The probability of getting a 6 when rolling a six-sided die 10 times

Should now read:

The probability of getting 6 k times when rolling a six-sided die 10 times

**Page 51:**

The line:

What we get in the end is a function that describes the probability of each possible hypothesis for our true belief in the probability of getting two heads from the box...

Should now read:

What we get in the end is a function that describes the probability of each possible hypothesis for our true belief in the probability of getting two coins from the box...

**Page 71:**

The equation:

numberOfRedStuds = P (yellow | red) × numberOfRedStuds = 1/5 × 20 = 4

Should now read:

numberOfRedUnderYellow = P(yellow | red) × numberOfRedStuds = 1/5 × 20 = 4

**Page 87:**

The equation:

Beta (20002,7401) = Beta (2 + 20000, 7400 + 1)

Should now read:

Beta (20002,7441) = Beta (2 + 20000, 7440 + 1)

**Page 88:**

The top label on Figure 9-3:

Distribution of our prior belief Beta(2+20000,7400+1)

Should now read:

Distribution of our posterior belief Beta(2+20000,7440+1)"

**Page 105:**

The last row of Table 11-1:

2.80. -0.16

Should now read:

2.80. -0.2

And the equation:

a<subscript 1> and b<subscript 1>

Should now read:

a<subscript i> and b<subscript i>

**Page 106:**

The second equation:

2.08

Should now read:

0.416

**Page 127:**

In the top code block, the second code line:

`xs.all <- seq(0,1,by=0.0001)`

Should be deleted

**Page 130:**

The reference to "Figure 3-5" should read "Figure 13-5"

**Page 164:**

The line:

The prior odds look like this:

Should now read:

The probabilities look like this:

And in the last equation, the fraction:

223/370,000

Should now read:

245/370,000

And the line:

This result shows that H2 is about 1,659 times more likely than H1.

Should now read:

This result shows that H2 is about 1,510 times more likely than H1.

**Page 224:**

The lines:

The slope of 5 means that for every time x grows by 1, y grows by 5; 4.8 is the point at which the line crosses the x-axis. In this example, we’d interpret this formula as s(t) = 5t + 4.8, meaning that for every mile you travel you accelerate by 5 mph, and that you started off at 4.8 mph. Since you’ve run half a mile, using this simple formula, we can figure out:

Should now read:

The slope of 5 means that for every time x grows by 1, y grows by 5; 4.8 is the point at which the line crosses the y-axis. In this example, we’d interpret this formula as s(t) = 5t + 4.8, meaning that for every mile you travel you accelerate by 5 mph, and that you started off at 4.8 mph. Since you’ve run half an hour, using this simple formula, we can figure out:

**Page 236:**

The line :

Luckily we already did all this work earlier in the chapter, so we know that (A) = 4/1,000 and P(B) = 3/(100,000).

Should now read:

Luckily we already did all this work earlier in the chapter, so we know that (A) = 8/100 and P(B) = 3/(100,000).

**Page 237:**

The line:

Plugging in our numbers, we get an answer of 100,747/25,000,000 or 0.00403.

Should now read:

Plugging in our numbers, we get an answer of 800,276/10,000,000 or 0.0800276.

**Page 242:** In the last line of code on the page, which reads:

`temp.sd <- my.sd(temp.data)`

Should read:

`temp.sd <- sd(temp.data)`

**Page 250:**

The second equation:

P (D | H2) = 0.63 × 0.55 × 0.49 = 0.170

Should now read:

P (D | H2) = 0.94 x 0.83 x 0.49 = 0.382

And the line:

This means that given the Bayes factor alone, vestibular schwannoma is a roughly two times better explanation than labyrinthitis. Now we have to look at the odds ratio:

Should now read:

This means that given the Bayes factor alone, vestibular schwannoma is a roughly four times better explanation than labyrinthitis. Now we have to look at the prior odds ratio:

**Page 251:**

The line:

The end result is that labyrinthititis is only a slightly better explanation than vestibular schwannoma.

Should now read:

The end result is that vestibular schwannoma is only a slightly better explanation than labyrinthitis.

**Page 254:**

In the top equation, the content should now read:

50 = 9/19 × BF BF = 950

And the second line of the first code block:

`hypotheses <- seq(0,1,by=0.01)`

Should now read:

`hypotheses <- seq(0,1,by=dx)`