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Congratulations! So far, you and your group members have read through the movie ideas and use data analysis to pick one movie you think will do best at the box office.

Data analysis like this is common in more than just the entertainment industry.

In the mid-nineties, the baseball team Oakland Athletics had a very low budget and could not hire standout players like other, more successful teams could.

Their general manager, Billy Beane took a new approach: he analyzed often-ignored data to pick players that other teams passed over.

He found player who looked like they would be unsuccessful according to traditional statistics, but actually had a good return on investment.

Beane constructed playoff teams in the early 2000's on just one third of the budget of other teams.

Other team managers, like Daryl Morey of the Houston Rockets basketball team, have applied analytics to other sports.

Morey even founded the MIT Sloan Sports Analytics Conference, where college students come together to discuss data analysis as it applies to baseball, basketball, football, hockey, and soccer.

Statistical analysis has changed the way people choose sports teams by revealing additional information that can be masked by more obvious or popular choices.

People use data in similar ways to help make decisions all the time: Meteorologists use data patterns to forecast the weather -- and you use their reports to decide what clothes to wear or whether to carry an umbrella.

Doctors collect vital signs and medical history to help determine the best treatment regimen or to predict the likelihood that you will develop certain illnesses.

You might even examine statistics when you draft your fantasy football or baseball teams or decide which players to bench.

In fact, you probably use data to make decisions more often than you think! But as you learned when selecting a movie to greenlight, data is only part of the decision-making process.

You cannot guarantee that it won't rain next Thursday or that you won't get high blood pressure or that a movie will be successful from collecting data-- even if the data strongly suggests that those things will happen.

Data can often be incomplete, messy, incorrect, or misleading.

So it's important to use data as only part of the decision-making process.

And of course, other factors go into making your movie a success.

In the next activities, you will design a poster that will make viewers want to see your movie, and you will test the effectiveness of your marketing materials.