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Technology is advancing at a rapid rate, changing various aspects of our everyday lives. Businesses and governments are trying to adapt to this change by embracing positive aspects, while remaining attentive to negative aspects. This note focuses on technologies such as artificial intelligence, machine learning, and big data, considering the ethical issues that these technologies create within our society and also how these ethical issues are being addressed.

Spreadsheet to accompany product 9B19E013.

An investment manager at Glitz Investments, a firm based in the United States with a focus on the entertainment industry, wanted to identify potential blockbuster movies in the Indian film industry for the firm’s potential investment purposes. The investment manager received a report compiled by analysts at the firm indicating that Bollywood would be an attractive industry for investment. The firm’s analysts had collected data but could the manager determine a quantitative relationship between box office performance and the factors the team had identified? Could Glitz Investments choose movies based on this analysis alone? The investment manager's boss was looking for more specific data on which to base the firm’s investment decisions.

Instructor Spreadsheet to accompany product 8B20E018.

In April 2020, amid the global pandemic resulting from the spread of Covid-19, the president of the Broadway League, which represented theatre owners, producers, presenters, and general managers for Broadway and across North America, faced a challenge. On March 12, 2020, Broadway had suspended all plays and musicals. The president and her team needed to determine when Broadway might be able to reopen, what the Broadway League should be communicating to producers and guests, and what the reopening of Broadway would look like amid the global coronavirus pandemic. However, to reach these decisions, she first needed to determine the reliability of the recently released New York State antibody study and estimate the true prevalence of antibodies in the population.

In April 2020, amid the global pandemic resulting from the spread of Covid-19, the president of the Broadway League, which represented theatre owners, producers, presenters, and general managers for Broadway and across North America, faced a challenge. On March 12, 2020, Broadway had suspended all plays and musicals. The president and her team needed to determine when Broadway might be able to reopen, what the Broadway League should be communicating to producers and guests, and what the reopening of Broadway would look like amid the global coronavirus pandemic. However, to reach these decisions, she first needed to determine the reliability of the recently released New York State antibody study and estimate the true prevalence of antibodies in the population.

Student spreadsheet to case W20558

In December 2019, a member of a fantasy hockey league had to decide whether to trade away his top talent in exchange for draft picks in the following year's fantasy draft or to continue to compete for a position in the playoffs. If he traded his top players, he would forfeit his chances at competing for a championship; however, this move might put his team in a better position for the following year's fantasy hockey season. He had access to the league's historical data to help determine the likelihood of his team making the playoffs. He wanted to conduct an analysis to make an informed decision grounded by numbers.

In December 2019, a member of a fantasy hockey league had to decide whether to trade away his top talent in exchange for draft picks in the following year’s fantasy draft or to continue to compete for a position in the playoffs. If he traded his top players, he would forfeit his chances at competing for a championship; however, this move might put his team in a better position for the following year’s fantasy hockey season. He had access to the league’s historical data to help determine the likelihood of his team making the playoffs. He wanted to conduct an analysis to make an informed decision grounded by numbers.

Instructor Spreadsheet to accompany product 8B20E013.

Spreadsheet to accompany product 9B20E013.

Student spreadsheet to case W19731

An investment manager at Glitz Investments, a firm based in the United States with a focus on the entertainment industry, wanted to identify potential blockbuster movies in the Indian film industry for the firm's potential investment purposes. The investment manager received a report compiled by analysts at the firm indicating that Bollywood would be an attractive industry for investment. The firm's analysts had collected data but could the manager determine a quantitative relationship between box office performance and the factors the team had identified? Could Glitz Investments choose movies based on this analysis alone? The investment manager's boss was looking for more specific data on which to base the firm's investment decisions.

In 2017, a sports journalist based in Houston, Texas was confused about his editor's latest idea. His editor had emailed him the night before proposing an article on the best (and worst) Major League Baseball hitters of all time. The first step was to provide a list of the players that would be profiled. This meant finding the 10 best (and worst) batters. However, after ranking the players, could he quantify the probability that he ranked them incorrectly? Because the article was based on data, he had to justify his choices and he wanted his decisions to be based on sound statistical grounds.

Student spreadsheet for case W18610

The purpose of this note is to explain the application areas of the chi-square goodness-of-fit test and how to run the test in Excel.

The purpose of this note is to explain the application areas of the chi-square goodness-of-fit test and how to run the test in Excel.

Spreadsheet to accompany product 9B18E015.

In 2017, a sports journalist based in Houston, Texas was confused about his editor’s latest idea. His editor had emailed him the night before proposing an article on the best (and worst) Major League Baseball hitters of all time. The first step was to provide a list of the players that would be profiled. This meant finding the 10 best (and worst) batters. However, after ranking the players, could he quantify the probability that he ranked them incorrectly? Because the article was based on data, he had to justify his choices and he wanted his decisions to be based on sound statistical grounds.

Instructor Spreadsheet to accompany product 8B18E015.