Basic requirements

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

Response:

- No
- Yes

Is the report anonymous?

Response:

- No
- Yes

Linear model: drowning data with Stan

Is the source code included?

Response:

- No
- Yes

Is the full resulting modiﬁed Stan model code presented in the report?

Response:

- No
- Yes

Fix #1: Is there a ﬁx for …

Response:

- It has not been discussed, that …
- It has been discussed, that … , but there is no ﬁx presented for it or the ﬁx is clearly wrong.
- There is a ﬁx presented for … , that clearly solves the problem.

Fix #2: Is there a ﬁx for …

Response:

- It has not been discussed, that …
- It has been discussed, that … , but there is no ﬁx presented for it or the ﬁx is clearly wrong.
- There is a ﬁx presented for … , that clearly solves the problem.

Fix #3: Is there a ﬁx for …

Response:

- It has not been discussed, that …
- It has been discussed, that … , but there is no ﬁx presented for it or the ﬁx is clearly wrong.
- There is a ﬁx presented for … , that clearly solves the problem.

Is there a suitable numerical value of approximately … presented for \(\sigma_beta\).

Response:

- No
- Yes

Does the report discuss and correctly present how the desired prior can be implemented in the model code.

Example implementation:

…

Another example implementation:

…

Response:

- No
- Yes

Does the report discuss and correctly present prior also for the intercept?

Example implementation:

…

Another example implementation:

…

Response:

- No
- Yes

Hierarchical model: factory data with Stan

Separate model: Is there a related Stan implementation (N.B. same implementation may be used for multiple models)?

Response:

- No Stan model implemented.
- Stan model implemented, but it seems clearly wrong or broken.
- Seemingly valid Stan model implemented.

Is the model described using mathematical notation?

Response:

- Yes
- No

Separate model: The following histograms are used as a reference in the grading of the separate model:

Separate model: *discussion about question i)*, posterior distribution of the mean of the quality measurements of the sixth machine.

Response:

*hidden responses*

Separate model: *discussion about question ii)*, the predictive distribution for another quality measurement of the sixth machine.

Response:

*hidden responses*

Separate model: *discussion about question iii)*, the posterior distribution of the mean of the quality measurements of the seventh machine.

Response:

*hidden responses*

Separate model: the posterior expectation for \(\mu_1\) with a 90% credibility interval using a N(0, 10) prior for \(\mu\) and a Gamma(1, 1) prior for \(\sigma\).

Response:

*hidden responses*

Pooled model: Is there a related Stan implementation (N.B. same implementation may be used for multiple models)?

Response:

- No Stan model implemented.
- Stan model implemented, but it seems clearly wrong or broken.
- Seemingly valid Stan model implemented.

Is the model described using mathematical notation?

Response:

- Yes
- No

Pooled model: The following histograms are used as a reference in the grading of the pooled model:

Pooled model: *discussion about question i)*, posterior distribution of the mean of the quality measurements of the sixth machine.

Response:

*hidden responses*

Pooled model: *discussion about question ii)*, the predictive distribution for another quality measurement of the sixth machine.

Response:

*hidden responses*

Pooled model: *discussion about question iii)*, the posterior distribution of the mean of the quality measurements of the seventh machine.

Response:

*hidden responses*

Pooled model: the posterior expectation for \(\mu_1\) with a 90% credibility interval using a N(0, 10) prior for \(\mu\) and a Gamma(1, 1) prior for \(\sigma\).

Response:

*hidden responses*

Hierarchical model: Is there a related Stan implementation (N.B. same implementation may be used for multiple models).

Response:

- No Stan model implemented.
- Stan model implemented, but it seems clearly wrong or broken.
- Seemingly valid Stan model implemented.

Is the model described using mathematical notation?

Response:

- Yes
- No

Hierarchical model: The following histograms are used as a reference in the grading of the hierarchical model:

Hierarchical model: *discussion about question i)*, posterior distribution of the mean of the quality measurements of the sixth machine.

Response:

*hidden responses*

Hierarchical model: *discussion about question ii)*, the predictive distribution for another quality measurement of the sixth machine.

Response:

*hidden responses*

Hierarchical model: *discussion about question iii)*, the posterior distribution of the mean of the quality measurements of the seventh machine.

Response:

*hidden responses*

Hierarchical model: the posterior expectation for \(\mu_1\) with a 90% credibility interval using a N(0, 10) prior for \(\mu\) and a Gamma(1, 1) prior for \(\sigma\).

Response:

*hidden responses*

Overall quality of the report

Does the report follow the formatting instructions?

- Not at all
- Little
- Mostly
- Yes

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.

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.