Estimation Calibration Vocabulary
Practice vocabulary for estimation calibration including velocity tracking, over-optimism, comparing estimates to actuals, and retrospective analysis of accuracy.
0 / 37 completed
1 / 37
When a team's sprint velocity closely matches its committed capacity sprint after sprint, we say the velocity _____.
Velocity tracking capacity closely indicates a well-calibrated team — their estimates match their actual throughput, making planning reliable.
2 / 37
A team that consistently commits to 40 points but only completes 32 is said to be _____.
Over-optimism in estimation means the team systematically commits to more work than they can deliver, often due to not accounting for interruptions, bugs, or complexity.
3 / 37
If historical data shows that estimates are consistently 30% lower than actual time spent, the team should _____.
A systematic bias of 30% off means estimates need a calibration correction. Teams should also investigate causes (underestimated complexity, interruptions) to improve future accuracy.
4 / 37
'Calibration' in the context of software estimation means _____.
Calibration is the practice of comparing estimates to actual outcomes, then adjusting estimation habits or correction factors to reduce systematic bias over time.
5 / 37
Which agile ceremony is the most appropriate place to discuss estimation accuracy and calibrate future estimates?
The retrospective is the dedicated ceremony for reflecting on process, including estimation accuracy — teams can discuss why estimates were off and agree on improvements.
6 / 37
Reviewer: 'The API response time is consistently higher than the target of 200ms. The team's initial estimate for this feature was 1 day. This isn't a huge problem, but we should investigate if our estimation techniques are accurate. Which of the following best describes the reviewer's concern regarding the situation?
This scenario highlights a common issue: inconsistent estimation. The reviewer's comment focuses on the discrepancy between the initial 1-day estimate and the actual API response time (significantly above 200ms). While overestimation *could* be a factor, the core problem is the lack of calibration – the team's current estimates aren't accurately reflecting reality. The options incorrectly frame the issue as simply 'slow' API or high velocity; it's about the mismatch between expectation and actual performance requiring adjustment.
7 / 37
Reviewer: 'The new user authentication service has an API response time averaging 800ms, significantly exceeding our target of 250ms. The team initially estimated this feature would take 3 days based on similar previous implementations. While the overall project is still on track, this performance discrepancy warrants investigation. Which of the following statements best reflects the reviewer's assessment of the situation regarding the estimation process?This scenario highlights a critical issue: consistently exceeding targets despite estimates. The reviewer isn't questioning the team's effort directly, but pointing out that an initial estimate of 3 days for a feature with an 800ms response time suggests a systematic underestimation of complexity – a key element of estimation calibration. Option A is incorrect because it ignores the performance data. Option C is also wrong as it dismisses the need to address the root cause. Therefore, option B correctly identifies the core problem: the team's estimation process isn't accurately reflecting the true effort required.
8 / 37
PR Description: "Implemented the user profile update feature. Took approximately 8 hours to complete, including testing."
During a code review, another developer comments: 'The initial estimate for this was 4 hours. It seems like we're consistently overestimating our time on smaller tasks. We should discuss this with the team to see if our approach needs adjustment.' What is the core issue highlighted in this comment?The comment isn't just about a single task taking longer than expected; it's focused on a pattern of overestimation. The developer recognizes that the team might be consistently underestimating the effort required for smaller tasks. This suggests a potential 'calibration' problem – the team isn't accurately gauging how much time they *really* need to complete work, and this needs to be addressed through discussion and potentially adjusting their estimation techniques.
9 / 37
Reviewer: 'The API response time is consistently higher than the target of 200ms. The team's initial estimate for this feature was 1 day. This isn't a huge problem, but we should investigate if our estimation techniques are accurate. Which of the following best describes the reviewer's concern regarding the situation?
This scenario highlights a common issue: inconsistent estimation. The reviewer's comment focuses on the discrepancy between the initial 1-day estimate and the actual API response time (significantly above 200ms). While overestimation *could* be a factor, the core problem is the lack of calibration – the team's current estimates aren't accurately reflecting reality. The options incorrectly frame the issue as simply 'slow' API or high velocity; it's about the mismatch between expectation and actual performance requiring adjustment.
10 / 37
Reviewer: 'The new user authentication service has an API response time averaging 800ms, significantly exceeding our target of 250ms. The team initially estimated this feature would take 3 days based on similar previous implementations. While the overall project is still on track, this performance discrepancy warrants investigation. Which of the following statements best reflects the reviewer's assessment of the situation regarding the estimation process?This scenario highlights a critical issue: consistently exceeding targets despite estimates. The reviewer isn't questioning the team's effort directly, but pointing out that an initial estimate of 3 days for a feature with an 800ms response time suggests a systematic underestimation of complexity – a key element of estimation calibration. Option A is incorrect because it ignores the performance data. Option C is also wrong as it dismisses the need to address the root cause. Therefore, option B correctly identifies the core problem: the team's estimation process isn't accurately reflecting the true effort required.
11 / 37
PR Description: "Implemented the user profile update feature. Took approximately 8 hours to complete, including testing."
During a code review, another developer comments: 'The initial estimate for this was 4 hours. It seems like we're consistently overestimating our time on smaller tasks. We should discuss this with the team to see if our approach needs adjustment.' What is the core issue highlighted in this comment?The comment isn't just about a single task taking longer than expected; it's focused on a pattern of overestimation. The developer recognizes that the team might be consistently underestimating the effort required for smaller tasks. This suggests a potential 'calibration' problem – the team isn't accurately gauging how much time they *really* need to complete work, and this needs to be addressed through discussion and potentially adjusting their estimation techniques.
12 / 37
Reviewer: 'The API response time is consistently higher than the target of 200ms. The team's initial estimate for this feature was 1 day. This isn't a huge problem, but we should investigate if our estimation techniques are accurate. Which of the following best describes the reviewer's concern regarding the situation?
This scenario highlights a common issue: inconsistent estimation. The reviewer's comment focuses on the discrepancy between the initial 1-day estimate and the actual API response time (significantly above 200ms). While overestimation *could* be a factor, the core problem is the lack of calibration – the team's current estimates aren't accurately reflecting reality. The options incorrectly frame the issue as simply 'slow' API or high velocity; it's about the mismatch between expectation and actual performance requiring adjustment.
13 / 37
Reviewer: 'The new user authentication service has an API response time averaging 800ms, significantly exceeding our target of 250ms. The team initially estimated this feature would take 3 days based on similar previous implementations. While the overall project is still on track, this performance discrepancy warrants investigation. Which of the following statements best reflects the reviewer's assessment of the situation regarding the estimation process?This scenario highlights a critical issue: consistently exceeding targets despite estimates. The reviewer isn't questioning the team's effort directly, but pointing out that an initial estimate of 3 days for a feature with an 800ms response time suggests a systematic underestimation of complexity – a key element of estimation calibration. Option A is incorrect because it ignores the performance data. Option C is also wrong as it dismisses the need to address the root cause. Therefore, option B correctly identifies the core problem: the team's estimation process isn't accurately reflecting the true effort required.
14 / 37
PR Description: "Implemented the user profile update feature. Took approximately 8 hours to complete, including testing."
During a code review, another developer comments: 'The initial estimate for this was 4 hours. It seems like we're consistently overestimating our time on smaller tasks. We should discuss this with the team to see if our approach needs adjustment.' What is the core issue highlighted in this comment?The comment isn't just about a single task taking longer than expected; it's focused on a pattern of overestimation. The developer recognizes that the team might be consistently underestimating the effort required for smaller tasks. This suggests a potential 'calibration' problem – the team isn't accurately gauging how much time they *really* need to complete work, and this needs to be addressed through discussion and potentially adjusting their estimation techniques.
15 / 37
Reviewer: 'The API response time is consistently higher than the target of 200ms. The team's initial estimate for this feature was 1 day. This isn't a huge problem, but we should investigate if our estimation techniques are accurate. Which of the following best describes the reviewer's concern regarding the situation?
This scenario highlights a common issue: inconsistent estimation. The reviewer's comment focuses on the discrepancy between the initial 1-day estimate and the actual API response time (significantly above 200ms). While overestimation *could* be a factor, the core problem is the lack of calibration – the team's current estimates aren't accurately reflecting reality. The options incorrectly frame the issue as simply 'slow' API or high velocity; it's about the mismatch between expectation and actual performance requiring adjustment.
16 / 37
Reviewer: 'The new user authentication service has an API response time averaging 800ms, significantly exceeding our target of 250ms. The team initially estimated this feature would take 3 days based on similar previous implementations. While the overall project is still on track, this performance discrepancy warrants investigation. Which of the following statements best reflects the reviewer's assessment of the situation regarding the estimation process?This scenario highlights a critical issue: consistently exceeding targets despite estimates. The reviewer isn't questioning the team's effort directly, but pointing out that an initial estimate of 3 days for a feature with an 800ms response time suggests a systematic underestimation of complexity – a key element of estimation calibration. Option A is incorrect because it ignores the performance data. Option C is also wrong as it dismisses the need to address the root cause. Therefore, option B correctly identifies the core problem: the team's estimation process isn't accurately reflecting the true effort required.
17 / 37
PR Description: "Implemented the user profile update feature. Took approximately 8 hours to complete, including testing."
During a code review, another developer comments: 'The initial estimate for this was 4 hours. It seems like we're consistently overestimating our time on smaller tasks. We should discuss this with the team to see if our approach needs adjustment.' What is the core issue highlighted in this comment?The comment isn't just about a single task taking longer than expected; it's focused on a pattern of overestimation. The developer recognizes that the team might be consistently underestimating the effort required for smaller tasks. This suggests a potential 'calibration' problem – the team isn't accurately gauging how much time they *really* need to complete work, and this needs to be addressed through discussion and potentially adjusting their estimation techniques.
18 / 37
During a standup meeting, Sarah says, "We estimated this new API endpoint would take 2 days to implement. However, we've spent the last three days debugging intermittent errors and optimizing for edge cases."
What does Sarah primarily mean when she discusses 'calibration' in this context?
'Calibration' refers to the process of regularly comparing actual outcomes with estimates to identify biases or inaccuracies. Option 2 accurately captures this – it highlights the need for ongoing review and adjustment based on historical data. Options A and D misinterpret calibration as solely adjusting time down; option B is too abstract.
19 / 37
A code reviewer sees a PR description stating: "Implemented user authentication flow. Took approximately 6 hours including testing."
The reviewer comments: 'The initial estimate for this was 2 days. This is a significant difference.' What potential issue does the reviewer highlight related to estimation?
The core problem is a difference in scale. A 6-hour task compared to a 2-day estimate indicates that the initial estimation process didn't account for the complexity or scope of the work effectively. This highlights a lack of calibration – the team's perception of effort didn't align with reality.
20 / 37
When discussing API response times that consistently exceed targets, a developer might say, 'We need to improve our estimation techniques and achieve better _______ – ensuring our estimates accurately reflect the actual effort required.'
'Accuracy' is the most appropriate term here. It directly relates to how closely an estimate matches the real outcome. 'Precision' refers to the level of detail; 'validation' is a process, and 'optimization' focuses on improving performance, not estimation itself.
21 / 37
During a Slack discussion about a delayed feature delivery, a senior engineer says: 'The team overestimated the complexity of integrating with the third-party library. We need to incorporate more data from previous sprints into our estimations to improve future _______'. What does 'calibration' refer to in this scenario?
'Calibration' in this context refers to adjusting the estimation model based on historical data. Using previous sprint data is a common technique for refining estimates and improving accuracy – it's about tuning the estimation process itself. The other options are related to different aspects of software development but aren't directly what 'calibration' means here.
22 / 37
A developer is reviewing a PR and notices the team estimated 5 days for a new data transformation service. After completion, it took only 3 days. What action would best demonstrate an understanding of 'calibration'?
The correct response is to analyze the situation and update the estimation model. 'Calibration' involves learning from past experiences – in this case, identifying what factors led to a more accurate estimate (potentially better understanding of the task or improved efficiency). Options A, B and D are inappropriate responses that don't address the core principle of calibration.
23 / 37
During a standup meeting, Sarah says, "We estimated this new API endpoint would take 2 days to implement. However, we've spent the last three days debugging intermittent errors and optimizing for edge cases."
What does Sarah primarily mean when she discusses 'calibration' in this context?
'Calibration' refers to the process of regularly comparing actual outcomes with estimates to identify biases or inaccuracies. Option 2 accurately captures this – it highlights the need for ongoing review and adjustment based on historical data. Options A and D misinterpret calibration as solely adjusting time down; option B is too abstract.
24 / 37
A code reviewer sees a PR description stating: "Implemented user authentication flow. Took approximately 6 hours including testing."
The reviewer comments: 'The initial estimate for this was 2 days. This is a significant difference.' What potential issue does the reviewer highlight related to estimation?
The core problem is a difference in scale. A 6-hour task compared to a 2-day estimate indicates that the initial estimation process didn't account for the complexity or scope of the work effectively. This highlights a lack of calibration – the team's perception of effort didn't align with reality.
25 / 37
When discussing API response times that consistently exceed targets, a developer might say, 'We need to improve our estimation techniques and achieve better _______ – ensuring our estimates accurately reflect the actual effort required.'
'Accuracy' is the most appropriate term here. It directly relates to how closely an estimate matches the real outcome. 'Precision' refers to the level of detail; 'validation' is a process, and 'optimization' focuses on improving performance, not estimation itself.
26 / 37
During a Slack discussion about a delayed feature delivery, a senior engineer says: 'The team overestimated the complexity of integrating with the third-party library. We need to incorporate more data from previous sprints into our estimations to improve future _______'. What does 'calibration' refer to in this scenario?
'Calibration' in this context refers to adjusting the estimation model based on historical data. Using previous sprint data is a common technique for refining estimates and improving accuracy – it's about tuning the estimation process itself. The other options are related to different aspects of software development but aren't directly what 'calibration' means here.
27 / 37
A developer is reviewing a PR and notices the team estimated 5 days for a new data transformation service. After completion, it took only 3 days. What action would best demonstrate an understanding of 'calibration'?
The correct response is to analyze the situation and update the estimation model. 'Calibration' involves learning from past experiences – in this case, identifying what factors led to a more accurate estimate (potentially better understanding of the task or improved efficiency). Options A, B and D are inappropriate responses that don't address the core principle of calibration.
28 / 37
During a standup meeting, Sarah says, "We estimated this new API endpoint would take 2 days to implement. However, we've spent the last three days debugging intermittent errors and optimizing for edge cases."
What does Sarah primarily mean when she discusses 'calibration' in this context?
'Calibration' refers to the process of regularly comparing actual outcomes with estimates to identify biases or inaccuracies. Option 2 accurately captures this – it highlights the need for ongoing review and adjustment based on historical data. Options A and D misinterpret calibration as solely adjusting time down; option B is too abstract.
29 / 37
A code reviewer sees a PR description stating: "Implemented user authentication flow. Took approximately 6 hours including testing."
The reviewer comments: 'The initial estimate for this was 2 days. This is a significant difference.' What potential issue does the reviewer highlight related to estimation?
The core problem is a difference in scale. A 6-hour task compared to a 2-day estimate indicates that the initial estimation process didn't account for the complexity or scope of the work effectively. This highlights a lack of calibration – the team's perception of effort didn't align with reality.
30 / 37
When discussing API response times that consistently exceed targets, a developer might say, 'We need to improve our estimation techniques and achieve better _______ – ensuring our estimates accurately reflect the actual effort required.'
'Accuracy' is the most appropriate term here. It directly relates to how closely an estimate matches the real outcome. 'Precision' refers to the level of detail; 'validation' is a process, and 'optimization' focuses on improving performance, not estimation itself.
31 / 37
During a Slack discussion about a delayed feature delivery, a senior engineer says: 'The team overestimated the complexity of integrating with the third-party library. We need to incorporate more data from previous sprints into our estimations to improve future _______'. What does 'calibration' refer to in this scenario?
'Calibration' in this context refers to adjusting the estimation model based on historical data. Using previous sprint data is a common technique for refining estimates and improving accuracy – it's about tuning the estimation process itself. The other options are related to different aspects of software development but aren't directly what 'calibration' means here.
32 / 37
A developer is reviewing a PR and notices the team estimated 5 days for a new data transformation service. After completion, it took only 3 days. What action would best demonstrate an understanding of 'calibration'?
The correct response is to analyze the situation and update the estimation model. 'Calibration' involves learning from past experiences – in this case, identifying what factors led to a more accurate estimate (potentially better understanding of the task or improved efficiency). Options A, B and D are inappropriate responses that don't address the core principle of calibration.
33 / 37
During a standup meeting, Sarah says, "We estimated this new API endpoint would take 2 days to implement. However, we've spent the last three days debugging intermittent errors and optimizing for edge cases."
What does Sarah primarily mean when she discusses 'calibration' in this context?
'Calibration' refers to the process of regularly comparing actual outcomes with estimates to identify biases or inaccuracies. Option 2 accurately captures this – it highlights the need for ongoing review and adjustment based on historical data. Options A and D misinterpret calibration as solely adjusting time down; option B is too abstract.
34 / 37
A code reviewer sees a PR description stating: "Implemented user authentication flow. Took approximately 6 hours including testing."
The reviewer comments: 'The initial estimate for this was 2 days. This is a significant difference.' What potential issue does the reviewer highlight related to estimation?
The core problem is a difference in scale. A 6-hour task compared to a 2-day estimate indicates that the initial estimation process didn't account for the complexity or scope of the work effectively. This highlights a lack of calibration – the team's perception of effort didn't align with reality.
35 / 37
When discussing API response times that consistently exceed targets, a developer might say, 'We need to improve our estimation techniques and achieve better _______ – ensuring our estimates accurately reflect the actual effort required.'
'Accuracy' is the most appropriate term here. It directly relates to how closely an estimate matches the real outcome. 'Precision' refers to the level of detail; 'validation' is a process, and 'optimization' focuses on improving performance, not estimation itself.
36 / 37
During a Slack discussion about a delayed feature delivery, a senior engineer says: 'The team overestimated the complexity of integrating with the third-party library. We need to incorporate more data from previous sprints into our estimations to improve future _______'. What does 'calibration' refer to in this scenario?
'Calibration' in this context refers to adjusting the estimation model based on historical data. Using previous sprint data is a common technique for refining estimates and improving accuracy – it's about tuning the estimation process itself. The other options are related to different aspects of software development but aren't directly what 'calibration' means here.
37 / 37
A developer is reviewing a PR and notices the team estimated 5 days for a new data transformation service. After completion, it took only 3 days. What action would best demonstrate an understanding of 'calibration'?
The correct response is to analyze the situation and update the estimation model. 'Calibration' involves learning from past experiences – in this case, identifying what factors led to a more accurate estimate (potentially better understanding of the task or improved efficiency). Options A, B and D are inappropriate responses that don't address the core principle of calibration.
Frequently Asked Questions
What does the "Estimation Calibration Vocabulary" exercise cover?
Practice vocabulary for estimation calibration including velocity tracking, over-optimism, comparing estimates to actuals, and retrospective analysis of accuracy.
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How many questions are in "Estimation Calibration Vocabulary"?
This exercise has 37 questions. Each one gives instant feedback with an explanation, so you can see exactly why an answer is right or wrong.
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