Which of the following statements accurately describe fairness considerations in data analysis? Select all that apply.

• Fairness means ensuring that analysis does not create or reinforce bias.

• A data professional may choose to use oversampling when prioritizing fairness.

• Best practices for fairness in data analysis include considering context.

• Fairness practices should begin during the process phase of the data analysis process.

A trucking company needs more drivers, so they purchase help-wanted ads online. Research reveals that 97% of truck drivers are men, so the data team decides that men are more likely to be successful applicants. Therefore, they target the ads to male job seekers. What should they have done instead?

• Conduct more research to understand the surrounding factors of this situation.

• Only target the ads for the trucking jobs to women.

• Find an additional data source that supports the strategy to target men.

• Ask the executive team to decide which type of applicants to target with the ads.

Which fairness best practice is intended to help data teams better understand the context surrounding their data analysis conclusions?

• Include self-reported data

• Identify surrounding factors

• Consider relevant data

• Use oversampling

While conducting a survey to learn about employee satisfaction, a data analyst notices that the majority of respondents are people who work in the operations department. The fairness of their survey could be improved by over-sampling which employees?

• People who have worked for the company less than five years

• People who have worked for the company more than five years

• People in operations who have not yet responded to the survey

• People who work in departments other than operations

Fill in the blank: Data analysts focus much of their time working on _____, which are the questions or problems that analysis can help address for an organization.

• measurable outcomes

• relevant processes

• business tasks

• stated objectives

A data professional at a grocery store considers fairness when collecting data. Rather than having store associates share observations, they create a survey that asks customers to provide information about their own shopping experiences. This helps avoid any unconscious bias that might be introduced by the sales associates. Which fairness best practice does this scenario describe?

• Using all available data

• Self-reporting

• Considering context

• Oversampling

A data analyst at a marketing company determines which advertising campaign will be most successful. Rather than only reviewing data about effective past campaigns, the analyst considers target audience demographics, market trends, competitor campaigns, and more. This enables them to achieve more insightful results. Which fairness best practice does this scenario describe?

• Oversampling

• Considering all available data

• Guiding business strategy

• Including self-reported data

Fill in the blank: A data professional ensures their data analysis is fair by considering fairness from _____ of a project.

• outlining to reporting

• beginning to conclusion

• planning to presentation

• analysis to completion