Predictive Analytics Concepts and Applications

Predictive analytics is a powerful technology that allows organizations to predict and influence future outcomes on an individual level. It is used across various sectors, including marketing, employment, and law enforcement, to improve operations and decision-making. The technology relies on vast amounts of stored data, raising ethical concerns about privacy and responsibility. The implementation of predictive analytics requires careful consideration to ensure it benefits society while addressing potential risks.

What is a key feature of predictive analytics that allows it to influence the future?

• It predicts outcomes for countries.

• It predicts outcomes for organizations.

• It predicts outcomes for individuals.

• It predicts outcomes for groups of people.

What is the main reason organizations use predictive analytics?

• To predict individual behaviors and outcomes.

• To predict weather patterns.

• To predict global economic trends.

• To predict stock market fluctuations.

How does predictive analytics help organizations?

• By decreasing their data storage.

• By reducing their workforce.

• By increasing their marketing budget.

• By improving their operational efficiency.

How does predictive analytics affect society?

• By reducing the quality of products.

• By increasing the cost of services.

• By improving how organizations serve individuals.

• By making organizations less efficient.

Why do companies prefer to store data rather than delete it?

• Because it is time-consuming to delete data.

• Because it is expensive to store data.

• Because it is cheap to store data.

• Because it is illegal to delete data.

What is a common practice among companies regarding data?

• They frequently delete old data.

• They sell data to competitors.

• They store data indefinitely.

• They ignore data from customers.

What does Hewlett Packard predict about its employees?

• Their likelihood of getting a promotion.

• Their likelihood of quitting their job.

• Their likelihood of getting a raise.

• Their likelihood of taking a vacation.

What is recidivism in the context of predictive analytics?

• Predicting if a student will fail a course.

• Predicting if an employee will resign.

• Predicting if a customer will return a product.

• Predicting if a felon will commit a crime again.

What is a potential risk associated with predictive analytics?

• It can result in biased decision-making.

• It can lead to increased data storage costs.

• It can reduce customer satisfaction.

• It can decrease organizational efficiency.

What is an ethical consideration in the use of predictive analytics?

• The complexity of algorithms used.

• The speed of data processing.

• The potential for misuse of predictive power.

• The cost of implementing the technology.