Asked in: Siemens
Image of the Question
All Testcases Passed ✔
Solution
def confidence(ratings):
# Write your code here
n = len(ratings)
ratings.sort()
// ... rest of solution available after purchaseExplanation
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To approach this problem, start by carefully understanding the scenario and the input format, then identify what exactly is being asked and what constraints or special cases may apply.
Step 1: Understand the input structure
- The input is a list representing participant confidence ratings.
- The first element of the list is not a confidence score but rather the total number of participants in the session.
- The subsequent elements represent the self-rated confidence scores of each participant, on a scale from 0 to 9.
- For example, if the list is [5, 7, 6, 8, 7, 5], the first element 5 means there are 5 participants, and their confidence scores are [7, 6, 8, 7, 5].
Step 2: Clarify what needs to be computed
- The goal is to find the overall confidence of the session, presumably based on the confidence ratings of participants.
- Since sessions are conducted in pairs, the overall confidence depends on how the participants are paired.
- The problem mentions an adjustment or a flowchart for when there is an odd number of participants.
- That suggests the approach to calculate overall confidence differs depending on whether the number of participants is even or odd.
Step 3: Consider the impact of pairing
- When participants are in pairs (even number), the average confidence might be calculated by averaging each pair’s scores or aggregating in some specific way.
- When participants are odd in number, the problem states there's a special flow to determine overall confidence.
- This special flow could involve averaging pairs and handling the leftover participant differently.
- Understanding this flow is crucial to handle the odd case correctly.
Step 4: Think about aggregation strategy
- Since confidence ratings are from 0 to 9, and you want an overall score, averaging is a natural method.
- For pairs, you might calculate the average of their two confidence scores.
- For odd participants, you might calculate averages of pairs and then combine the leftover participant’s score separately.
- The flowchart likely specifies rules on how to merge these averages or how to treat the single leftover participant.
Step 5: Plan for the calculation
- Extract the number of participants from the first element.
- Extract the confidence scores accordingly.
- Group participants into pairs:
- For even number of participants, form N/2 pairs.
- For odd number, form (N-1)/2 pairs and have one leftover participant.
- Calculate each pair’s combined confidence score, maybe as an average or some other measure specified.
- For the odd leftover participant, follow the flowchart’s instructions to integrate their score with the pairs’ scores.
Step 6: Handle the output format
- The problem might require returning the overall confidence as a single value.
- This might be a number representing average confidence across pairs (and the leftover if odd).
- Ensure the output respects the problem’s precision requirements, like integer or float.
Step 7: Consider edge cases
- What if the number of participants is zero or one? How should the confidence be handled?
- What if all confidence scores are the same? Confirm that the calculation behaves correctly.
- If the confidence scores contain minimum (0) or maximum (9) values, verify that the method accounts for extremes.
Step 8: Reflect on computational complexity
- The operations involve grouping participants into pairs and averaging, which can be done in a single pass.
- The complexity should be linear in the number of participants.
- No heavy computations or complex data structures are needed.
Step 9: Summarize approach
- Extract participant count and confidence ratings.
- For even counts, pair participants straightforwardly and calculate overall average.
- For odd counts, pair participants, compute averages, and then use the specified flowchart steps to integrate the leftover participant’s confidence score.
- Return the calculated overall confidence value.
By following this structured approach—understanding input format, managing pairs, handling odd participant scenarios, and averaging correctly—you will be able to determine the overall confidence of the coding session effectively.
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