# Assignment 3

## S1 - 7.5 points

Basic requirements

### Q1 - 1 point

Can you open the pdf and it’s not blank?

• No
• Yes

### Q2 - 1 point

Is the report anonymous?

• No
• Yes

## S2 - 28.3 points

Exercise 1

### Q3 - 1 point

Is the source code included?

• No
• Yes

### Q4 - 1 point

Are the likelihood, prior and the posterior for computing the average hardness value reported? It is ok to refer to the book instead of deriving the distributions.

• No
• Yes, but some are missing
• Yes

### Q5 - 1 point

In part a), were the point estimates and posterior interval provided? (The posterior mean should be close to … and 95% posterior interval should be around […, …])

• No
• Yes, but seem incorrect or only one estimate was reported
• Yes, and the reported values seem plausible

### Q6 - 1 point

In part a), was the density plotted?

• No
• Yes, but seem incorrect
• Yes, and the plot seems plausible

### Q7 - 1 point

For b)-part, was a formula or a simulation method presented for computing the posterior predictive distribution? It is ok to refer to the book.

• No
• Yes, but seems incorrect
• Yes

### Q8 - 1 point

For b)-part, were the point estimate and predictive interval provided? (95% predictive interval should be around […,…] and the mean the same as in part a).

• No
• Yes, but seems incorrect
• Yes, and the reported values seem plausible

### Q9 - 1 point

For b)-part, was the density plotted?

• No
• Yes, but seems incorrect
• Yes, and the plot seem plausible

## S3 - 28.3 points

Exercise 2

### Q10 - 1 point

Is the source code included?

• No
• Yes

### Q11 - 1 point

Are the likelihood, prior and the posterior for the death probabilities reported? It is ok to refer to the book instead of deriving the distributions.

• No
• Yes, but some are missing
• Yes

### Q12 - 1 point

In part a), was the simulation algorithm for computing the posterior of the odds ratio presented or implemented?

• No
• Yes, but seems incorrect
• Yes

### Q13 - 1 point

In a)-part, was the odds ratio summarized with a point estimate and a posterior interval? (The mean should be close to … and 95% posterior interval approximately […, …])

• No
• Yes, but results seem incorrect
• Yes, and the results seem plausible

### Q14 - 1 point

In part b), was some discussion about testing alternative priors provided?

• Not at all
• Some analysis was provided but it was lacking or did not make sense
• Some alternative priors were tested and some sensible discussion provided

## S4 - 28.3 points

Exercise 3

### Q15 - 1 point

Is the source code included?

• No
• Yes

### Q16 - 1 point

Are the likelihood, prior and the posterior for the windshield hardness values reported? (It is ok to refer to the book or related formulas from exercise 1)

• No
• Yes, but some are missing
• Yes

### Q17 - 1 point

In part a), was the simulation algorithm for computing the difference in the means presented or implemented?

• No
• Yes, but seems to be incorrect
• Yes

### Q18 - 1 point

In part a), was the posterior for the difference between the means summarized with point and interval estimates? (The mean should be close to … and 95% posterior interval […, …] or something close to it)

• Yes, but results seem incorrect or only one estimate was given
• Yes, and results seem reasonable

### Q19 - 1 point

Was some analysis and discussion provided for assessing whether the means could be the same?

• No
• Yes, but the analysis or explanation seems incorrect
• Yes

## S5 - 7.5 points

Overall quality of the report

### Q20 -

Does the report follow the formatting instructions?

• Not at all
• Little
• Mostly
• Yes

### Q21 -

In case the report doesn’t fully follow the formatting instructions, specify the formatting instruction that is not followed. If applicable, specify the page of the report, where this difference in formatting is visible.

### Q22 -

Please provide also feedback on the presentation (e.g. text, layout, flow of the responses, figures, figure captions). Part of the course is practicing making data analysis reports. By providing feedback on the report presentation and other students can learn what they can improve or what they already did well. You should be able to provide constructive or positive feedback for all non-empty reports, even if there is nothing to say about the technical correctness of the answers. You can also provide feedback on code.