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The Influence of Peers "If Johnny jumps off a cliff are you going to jump, too"? This is a cliché used often by parents wanting to convince their children that doing what "everyone else does" is not always a good idea.   For example, binge drinking is an increasing problem on college campuses, often with dire consequences (e.g., alcohol poisoning, unprotected sex, expulsion from school). Given the consequences, one wonders what compels college students to engage in such risky behavior. We know that fitting in—being accepted by others—is a primary motive for doing what others do. In this case, conforming to one’s referent group’s norms (i.e., getting drunk is cool) gains one’s acceptance to that group (Talbott, Wilkinson, Moore, & Usdan, 2014; Wardell & Read, 2013). Refusal to comply means rejection by the group. Binge drinking, clearly, is not in the best interest of individual college students, unless you consider the importance of belonging to and acceptance by the group. For this Discussion, you explore persuasion strategies with respect to the effects of peer influence on behavior.   Review the Learning Resources for this week and examine how social psychology theory and research explain the effects of peer influence on behavior. Consider persuasion strategies that a social psychologist might use to convince someone to defy peer pressure. Post an explanation for how you might persuade someone to "do what is in her or his best interest" when it means defying group demands. Use social psychology theory and research to support your persuasion strategy.  Social Loafing Brian, a class colleague, is someone who counts on the group's high achievers to do the majority of the work. This behavior is known as social loafing. Social loafers thrive because they know the high achievers cannot do less than their best; that is precisely what makes them high achievers. Adding to the problem, if it is the group product that is evaluated rather than individual contributions—then Brian will be less motivated to participate. That is why social loafing is rampant in university classrooms where grades are based on the finished group product. For this Discussion, you examine methods to motivate social loafers.  Review the Learning Resources for this week and consider motivation methods that a social psychologist might use to encourage a social loafer to do his or her share. Recall a time when you observed social loafing. Post a situation when you experienced or observed social loafing. Informed by social psychology theory, suggest ways to motivate social loafers to carry their weight Possible References: Underwood, M. K., & Ehrenreich, S. E. (2014). Bullying May Be Fueled by the Desperate Need to Belong. Theory Into Practice, 53(4), 265–270. Sonnentag, T., & Barnett, M. (2013). An Exploration of Moral Rebelliousness with Adolescents and Young Adults. Ethics & Behavior, 23(3), 214–236. 





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Why Perfect Predictions Are Impossible—And Why We Still Use Data Anyway

In Sebastian Wernicke’s TED Talk, How to Use Data to Make a Hit TV Show, he highlights both the power and the limitations of data-driven decision-making in the entertainment industry. While data can uncover patterns and support decisions, it cannot perfectly predict the success of a television show—or any complex human-centered outcome. This limitation persists even when we possess large volumes of accurate, high-quality data. Wernicke’s presentation, though humorous and engaging, opens up a deeper conversation about the limits of data analytics and the continued importance of data in forecasting, especially in dynamic and creative fields like entertainment.

The Limitations of Predictive Data

One core reason perfect prediction is unattainable, even with comprehensive data, is the complexity of human behavior. People are not machines—they have emotions, cognitive biases, evolving preferences, and cultural influences that can shift dramatically over time. These human elements introduce non-linear variables that are extremely difficult to quantify, let alone predict with consistent accuracy. For instance, a show might perform poorly during its original airing but gain a cult following years later due to changes in social values or rediscovery through online platforms (e.g., Arrested Development or Firefly). These types of outcomes defy initial data-based predictions.

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