Bring ideas together without being told which method to use. Show the reasoning that makes your result valid.
Suggested session length: 120 minutes, as an unvalidated planning estimate. This collection contains 4 tasks; choose a manageable set and return for further sessions. Completing the whole collection may take substantially longer. This is a unit assessment, not a full course or AP examination.
Show the design, response support and intermediate score or information calculations.
Public synthetic tasks and suggested time are practice, not an independently validated examination. State existence, numerical stopping and inferential conditions separately.
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0 of 4 tasks have recorded responses. No overall mastery score is assigned.
Independent groups at x=−1,0,1 have totals 8 and successes 2,4,6. Derive the finite logistic MLE, information and the initial Newton step from zero. State what guarantees existence and what an optimizer still has to check.
Structure your argument and preserve revisions
These optional planning fields save locally. Recording your response saves an immutable copy of the argument and these fields. Older records may contain only first/latest responses; missing intermediate revisions are not reconstructed.
Each field allows 2,000 characters. Keep a specific claim, state where it applies, cite the facts you use, and explain what still needs checking. Blank fields are allowed and are not evidence of mastery.
Poisson counts (2,4,8) at exposures (1,2,4) are fitted by a constant rate. Derive the likelihood maximizer, link information and asymptotic 95% rate interval. Then change the last count to zero and explain why the positive-total case still has a finite MLE.
Structure your argument and preserve revisions
These optional planning fields save locally. Recording your response saves an immutable copy of the argument and these fields. Older records may contain only first/latest responses; missing intermediate revisions are not reconstructed.
Each field allows 2,000 characters. Keep a specific claim, state where it applies, cite the facts you use, and explain what still needs checking. Blank fields are allowed and are not evidence of mastery.
A logistic design has an intercept and predictors x and 2x. Pure failures occur at negative x and pure successes at positive x. A program prints a large coefficient after reaching its cap. Identify three distinct issues and show that dropping the duplicate column does not fix them all.
Structure your argument and preserve revisions
These optional planning fields save locally. Recording your response saves an immutable copy of the argument and these fields. Older records may contain only first/latest responses; missing intermediate revisions are not reconstructed.
Each field allows 2,000 characters. Keep a specific claim, state where it applies, cite the facts you use, and explain what still needs checking. Blank fields are allowed and are not evidence of mastery.
A frozen Poisson rate is 2 per hour. At exposure 3 hours, a new count is 9. Compute the count mean and Pearson contribution. A revision sets its rate to 3 using that outcome. Compare log losses up to common factorial terms and write a valid evaluation conclusion.
Structure your argument and preserve revisions
These optional planning fields save locally. Recording your response saves an immutable copy of the argument and these fields. Older records may contain only first/latest responses; missing intermediate revisions are not reconstructed.
Each field allows 2,000 characters. Keep a specific claim, state where it applies, cite the facts you use, and explain what still needs checking. Blank fields are allowed and are not evidence of mastery.
Review and revisit
Use each rubric to identify a valid argument, a missing condition or a step to revise. For independent evaluation, ask a teacher or reviewer to examine the complete reasoning. Self-review and recorded responses are not verified assessment results.
Coverage and targeted lesson returns
Independent groups at x=−1,0,1 have totals 8 and successes 2,4,6. Derive the finite logistic MLE, information and the initial Newton step from zero. State what guarantees existence and what an optimizer still has to check.
Poisson counts (2,4,8) at exposures (1,2,4) are fitted by a constant rate. Derive the likelihood maximizer, link information and asymptotic 95% rate interval. Then change the last count to zero and explain why the positive-total case still has a finite MLE.
A logistic design has an intercept and predictors x and 2x. Pure failures occur at negative x and pure successes at positive x. A program prints a large coefficient after reaching its cap. Identify three distinct issues and show that dropping the duplicate column does not fix them all.
A frozen Poisson rate is 2 per hour. At exposure 3 hours, a new count is 9. Compute the count mean and Pearson contribution. A revision sets its rate to 3 using that outcome. Compare log losses up to common factorial terms and write a valid evaluation conclusion.
