Data Bias Quiz Form
Test your understanding of data bias with these scenario-based questions. Select the best answer for each.
Which of the following best defines data bias?
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A systematic error introduced by the way data is collected or processed.
Random variation in data due to chance.
Errors caused by software bugs.
Deliberate falsification of results.
Select all sources that can introduce bias into a dataset.
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Sampling methods
Survey question wording
Data cleaning procedures
Random number generation
Data labeling practices
A hiring algorithm is trained on historical company data where most hires were male. What type of bias is this most likely to introduce?
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Selection bias
Algorithmic bias
Measurement bias
No bias
On a scale from 1 (Not at all likely) to 5 (Extremely likely), how likely is it that biased training data will affect the fairness of a predictive model?
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Not at all likely
1
2
3
4
Extremely likely
5
1 is Not at all likely, 5 is Extremely likely
Which scenario illustrates confirmation bias in data analysis?
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Only searching for evidence that supports a hypothesis.
Randomly splitting data into training and test sets.
Applying standard data normalization techniques.
Reporting all results, regardless of outcome.
Select all actions that can help reduce data bias.
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Diversify data sources
Audit and review datasets regularly
Ignore outliers
Document data collection methods
Use representative samples
Briefly describe an example of unintentional data bias you have encountered or studied.
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What is the main risk of ignoring bias in data-driven decision-making?
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Unfair or inaccurate outcomes
Faster decision-making
Reduced data storage needs
Improved data privacy
How confident are you in your ability to identify data bias in a new dataset?
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Not confident
1
2
3
4
Very confident
5
1 is Not confident, 5 is Very confident
In a sentence or two, explain why addressing data bias is important in machine learning projects.
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