Assignment 7

S1 · 7.5 points

Basic requirements

Q1 · Yes / No · 1 points

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

Response:

  • No
  • Yes

Q2 · Yes / No · 1 points

Is the report anonymous?

Response:

  • No
  • Yes

S2 · 42.5 points

Linear model: drowning data with Stan

Q3 · Yes / No · 1 point

Is the source code included?

Response:

  • No
  • Yes

Q4 · Yes / No · 1 point

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

Response:

  • No
  • Yes

Q5 · Scale · 1 point

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.

Q6 · Scale · 1 point

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.

Q7 · Scale · 1 point

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.

Q8 · Yes / No · 1 point

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

Response:

  • No
  • Yes

Q9 · Yes / No · 1 point

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

Q10 · Yes / No · 1 point

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

Example implementation:

Another example implementation:

Response:

  • No
  • Yes

S3 · 42.5 points

Hierarchical model: factory data with Stan

Q11 · Scale · 1 point

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.

Q12 · Scale · 1 point

Is the model described using mathematical notation?

Response:

  • Yes
  • No

Explanation

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

Q13 · Yes / No · 1 point

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

Response:

hidden responses

Q14 · Yes / No · 1 point

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

Response:

hidden responses

Q15 · Yes / No · 1 point

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

Response:

hidden responses

Q16 · Yes / No · 1 point

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

Q17 · Scale · 1 point

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.

Q18 · Scale · 1 point

Is the model described using mathematical notation?

Response:

  • Yes
  • No

Explanation

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

Q19 · Scale · 1 point

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

Response:

hidden responses

Q20 · Scale · 1 point

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

Response:

hidden responses

Q21 · Yes / No · 1 point

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

Response:

hidden responses

Q22 · Yes / No · 1 point

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

Q23 · Scale · 1 point

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.

Q24 · Scale · 1 point

Is the model described using mathematical notation?

Response:

  • Yes
  • No

Explanation

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

Q25 · Scale · 1 point

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

Response:

hidden responses

Q26 · Scale · 1 point

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

Response:

hidden responses

Q27 · Scale · 1 point

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

Response:

hidden responses

Q28 · Yes / No · 1 point

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

S4 · 7.5 points

Overall quality of the report

Q29 · Scale · 1 point

Does the report follow the formatting instructions?

  • Not at all
  • Little
  • Mostly
  • Yes

Q30 -

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.

Q31 -

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.