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Research Methodology (MESIGP470425)

Research Methodology (MESIGP470425)

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Survivorship bias is the error of:

Choosing samples out of convenience

Focusing only on failures to understand what went wrong

Giving too much weight to negative feedback

Learning only from successful outcomes while ignoring the failures

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What is the key difference between random error and systematic bias?

Random error is intentional, while bias is always unconscious

More data can fix random error, but it will only reinforce bias

Random error affects accuracy, while bias affects precision

Bias can be managed with larger sample sizes, but random error cannot

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Which of the following is an example of conscious bias mentioned in the text?

Cognitive blind spots

"Cherry-picking" data to support a hypothesis

Confirmation bias

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What is the purpose of "blinding" in data collection?

To remove outliers from the dataset

To test the model's performance in low-light conditions

To speed up the data labeling process

To hide contextual information from human labelers to prevent their judgment from being influenced

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What is a "Living Labeling Guide"?

A list of all the data sources used in a project

A report detailing the project's final conclusions

A document that tracks the performance of a model over time

A Standard Operating Procedure (SOP) with clear definitions and visual examples for data annotators

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What is selection bias?

A flaw in the sampling method where the sample is not representative of the whole population

Learning only from successes and ignoring failures

Inconsistent choices made during data labeling

A tendency to favor data that aligns with pre-existing beliefs

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What is exclusion bias?

The inconsistent labeling of data

The tendency to focus only on successful examples

A flaw in the data collection method

The systematic removal of certain data points, which inadvertently strips out vital information

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What is a key mitigation strategy for selection bias during data collection?

Relying on the most easily accessible data

Using robust sampling techniques like random or stratified sampling

Collecting as much data as possible from a single source

Using convenience sampling

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You are building a model to identify toxic comments online. Which of the following is a necessary step to avoid evaluation bias?

Check the model's performance on comments related to different sensitive topics and demographic groups

Only use data that has been labeled by at least three different people

Ensure the model has an overall accuracy of at least 99%

Use the most complex deep learning architecture available

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Which phase of the technical lifecycle is most susceptible to introducing bias through subjective choices disguised as objective "cleaning"?

Collection Phase

Communication Phase

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