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

Recently, you were presented with cases about data analytics in the real world. One case involved an unfair conclusion about the performance of women who worked at a business. It demonstrated that data can sometimes be true, yet unfair. In addition, it highlighted the importance of asking, "Why?" when reviewing the results of data analysis.Another example involved data analysts prioritizing fairness and going out of their way to ensure their data was as fair as possible. Because they were working with sensitive and potentially biased health data, they chose to collaborate with social scientists in order to better understand the social context behind that data. If you need to, return to the video to refresh your understanding of the examples before you continue. Then, discuss the first case and how the analysts at that company could improve their process:What could they have done differently to be fairer in their analysis? What could have made their conclusion less biased? Submit two or more paragraphs (100-200 words total)

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

Why should a data analyst only ask fair questions?1 pointFair questions do not offend people.Fair questions are biased.Unfair questions do not have answers.Unfair questions can provide data that is misleading.

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