Which of the following are examples of fairness in data analysis? Select all that apply. 1 pointConsidering systematic factors that may influence dataFactoring in social contexts that could create bias in conclusionsPicking and choosing which data to include from a datasetMaking sure a sample population represents all groups

Question 1Which of the following statements accurately describe fairness considerations in data analysis? Select all that apply.1 pointBest practices for fairness in data analysis include identifying surrounding factors.Fairness practices should begin during the analyze phase of the data analysis process.Effective data analysts help create systems that are fair and inclusive to everyone. A data professional may include self-reported data when prioritizing fairness.

Question 3Which fairness best practice is intended to help data teams better understand the context surrounding their data analysis conclusions?1 pointUse oversamplingConsider relevant dataIdentify surrounding factorsInclude self-reported data

Question 6Data analysts ensure their analysis is fair for what reason?1 pointFairness helps them avoid biased conclusions.Fairness helps them pick and choose which data to include from a dataset. Fairness helps them communicate with stakeholders.Fairness helps them stay organized.

What are the examples of fair or unfair practices?How could a data analyst correct the unfair practices?

Question 8Fill in the blank: A data professional ensures their data analysis is fair by considering fairness from _____ to the point when their organization acts on the data insights. 1 pointthe data-collection phase of a projectthe insight-sharing phase of a projectthe start of a projectthe data-cleaning phase of a project