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SMU: Stars Café
SMU: Stars Café APK
51 ․ 5 years agoFree ․ Singapore Management University ⇣ Download APK (38.30 MB)
Experiment with food trends & cost cutting measures for statistical excellence!
What's SMU: Stars Café APK?
SMU: Stars Café is a app for Android, It's developed by Singapore Management University author.
First released on google play in 6 years ago and latest version released in 5 years ago.
This app has 151 download times on Google play
This product is an app in Educational category. More infomartion of SMU: Stars Café on google play
Welcome to the STARS Café. Take charge of a nation-wide café chain as you experiment with different food trends and cost cutting measures, all in the name of statistical excellence!
Run tests on over 30 delicious scenarios! Make decisions affecting your entire café chain! Will you emerge as the most profitable café? Or will you drive your business to the ground?
Learning Objectives
-Applied Learning of Research Design Concepts: by pilot testing new product changes and deciding whether or not to roll them out to the entire chain of cafes, players learn the consequences of Type I and Type II errors and the factors that influence statistical power.
-Self-Reflection: Feedback during and after the game allows the player to reflect on their own performance; they learn how sample size and effect size can influence their ability to detect reliable effects, which can help them improve their performance on future plays of the game.
Run tests on over 30 delicious scenarios! Make decisions affecting your entire café chain! Will you emerge as the most profitable café? Or will you drive your business to the ground?
Learning Objectives
-Applied Learning of Research Design Concepts: by pilot testing new product changes and deciding whether or not to roll them out to the entire chain of cafes, players learn the consequences of Type I and Type II errors and the factors that influence statistical power.
-Self-Reflection: Feedback during and after the game allows the player to reflect on their own performance; they learn how sample size and effect size can influence their ability to detect reliable effects, which can help them improve their performance on future plays of the game.
