-
Notifications
You must be signed in to change notification settings - Fork 5
/
Lecture_08_01_Bayesian_Thinking.Rmd
76 lines (59 loc) · 3.8 KB
/
Lecture_08_01_Bayesian_Thinking.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
## Lecture 8.1: Bayesian Thinking {#bayes}
<!-- reference with [Bayesian thinking](#bayes) -->
Welcome to **Decision Analysis and Forecasting for Agricultural Development**. Feel free to bring up any questions or concerns in the Slack or to [Dr. Cory Whitney](mailto:cory.whitney@uni-bonn.de?subject=[Lecture_6]%20Decision%20Analysis%20Lecture) or the course tutor.
Please watch the video and answer the multiple choice questions below.
<!-- https://youtu.be/_Hf7tYwTEZw -->
<iframe width="560" height="315" src="https://www.youtube.com/embed/_Hf7tYwTEZw" frameborder="0" allowfullscreen></iframe>
```{r bayesian-thinking-question-1, echo=FALSE}
question("What are characteristics of the frequentist approach to science?",
answer("We should consider prior knowledge."),
answer("All knowledge should be derived objectively from data.", correct = TRUE),
answer("Research can not produce insights into causal relationships.", correct = TRUE),
incorrect = "Watch [the talk](https://youtu.be/_Hf7tYwTEZw) and try again.",
allow_retry = TRUE
)
```
```{r bayesian-thinking-question-2, echo=FALSE}
question("What are the main challenges to Bayesian science today?",
answer("Lack of computational power."),
answer("Reliable characterization of the state of knowledge, i.e. definition of good Bayesian priors", correct = TRUE),
answer("The scientific community does not accept Bayesian methods."),
incorrect = "Watch [the talk](https://youtu.be/_Hf7tYwTEZw) and try again.",
allow_retry = TRUE
)
```
```{r bayesian-thinking-question-3, echo=FALSE}
question("What is a Bayesian Prior?",
answer("A probability distribution that expresses beliefs about a quantity before some evidence is taken into account.", correct = TRUE),
answer("The understanding about a phenomenon before any research or formal data collection.", correct = TRUE),
answer("An expression of the existing state of knowledge that takes into account all existing data and available knowledge.", correct = TRUE),
answer("A good reflection of reality based on the existing state of knowledge.", correct = TRUE),
incorrect = "Watch [the talk](https://youtu.be/_Hf7tYwTEZw) and try again.",
allow_retry = TRUE
)
```
```{r bayesian-thinking-question-4, echo=FALSE}
question("What is a posterior belief?",
answer("Revised or updated probability after taking into consideration new information.", correct = TRUE),
answer("Updated understanding after having applied some observations or research to our prior belief.", correct = TRUE),
answer("An expression of a belief that is the result of long term trials and investigations."),
answer("Updated beliefs about values and events after having seen additional information.", correct = TRUE),
answer("It is the prior probability plus new evidence.", correct = TRUE),
incorrect = "Watch [the talk](https://youtu.be/_Hf7tYwTEZw) and try again.",
allow_retry = TRUE
)
```
```{r bayesian-thinking-question-5, echo=FALSE}
question("What are ways that we can define proper priors?",
answer("Perform long term trials to generate a data set from which to generate reliable values."),
answer("Consider your prior beliefs about the distribution of the parameters.", correct = TRUE),
answer("Calibrate ourselves and others who are expected to express knowledge.", correct = TRUE),
answer("Use your intuitive understanding to generate a distribution.", correct = TRUE),
incorrect = "Watch [the talk](https://youtu.be/_Hf7tYwTEZw) and try again.",
allow_retry = TRUE
)
```
![](images/bayesian-hypothesis-testing.jpg){width=2in}
Summarize for yourself the difference between the frequentist and the Bayesian approach to knowledge generation. Which one do you feel more comfortable about? Are you ready to become a Bayesian?
### Group discussion reading:
- Bertsch McGrayne (2011) `The theory that would not die’ (Chapter 1. Causes in the Air)