Level 2
Problem Solving & Data Reasoning
Learn to frame problems clearly, solve them in structure, and avoid weak data reasoning.
Outcome
You learn to frame the real question, decompose it, and avoid common interpretation mistakes.
Coverage
4 topics | 8 questions
Level Structure
0% completed
Topic 1
Problem Framing (GAI)
2 questions
Topic 2
Structured Solving
2 questions
Topic 3
Data Interpretation
2 questions
Topic 4
Reasoning Patterns
2 questions
Topic Library
Learn the concept, then solve the questions
2 Questions
Problem Framing (GAI)
2 Questions
Problem Framing (GAI)
Problem Framing (GAI)
- Given means the explicit facts, constraints, and hard data that define the starting point.
- Asked means the real decision question, which is often deeper than the first version stated aloud.
- Implied means the hidden assumptions that quietly shape the answer unless they are examined.
Pause & Think
Before answering, list what is given, what is truly being asked, and what is only implied.
Question 1
A client asks, 'How do we reduce costs?' but the better reframe may be 'How do we add more value with existing resources?' Which part of GAI is doing the most work in that shift?
Question 2
A team lists all the hard numbers and rules in a case but never surfaces stakeholder beliefs or assumptions about what must stay constant. Which GAI element is being neglected?
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2 Questions
Structured Solving
2 Questions
Structured Solving
Structured Solving
- A hard problem becomes manageable when it is broken into drivers that can be tested one by one.
- Case-based reasoning helps because familiar structures reveal what type of answer is likely to matter.
- Elimination is not guessing; it is removing options that conflict with facts, constraints, or logic.
Pause & Think
Pause before solving and decide what the main buckets or drivers are before you chase details.
Question 1
When a problem feels large and vague, which first move best matches this framework's structured solving approach?
Question 2
Which action best reflects elimination techniques in this framework?
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2 Questions
Data Interpretation
2 Questions
Data Interpretation
Data Interpretation
- Data becomes dangerous when patterns are accepted before checking how the pattern was produced.
- Correlation, misleading averages, and aggregated views can hide the real signal if subgroup logic is ignored.
- A better habit is to ask what the full dataset, the base rate, and the missing observations would say.
Pause & Think
Before locking an answer, ask whether you are seeing causation, the full dataset, and the right subgroup view.
Question 1
Ice cream sales and drownings both rise in summer. In this topic, what is the correct interpretation?
Question 2
A trend appears positive in each subgroup but reverses when all groups are combined. Which trap is this in this topic?
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2 Questions
Reasoning Patterns
2 Questions
Reasoning Patterns
Reasoning Patterns
- Many difficult sets become easier once you identify whether the structure is arrangement, network, game, or flow.
- The surface story changes, but the constraint logic underneath is often the same across problems.
- Good solvers track relationships and movement carefully instead of restarting their thinking from zero each time.
Pause & Think
Pause before solving and ask whether the problem is mainly about ordering, connections, competition, or tracking movement.
Question 1
If a problem asks who sits where under multiple seating constraints, which pattern from this topic is the best starting frame?
Question 2
A puzzle asks you to track how quantity moves across several connected points over time. Which pattern best fits in this topic?
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