4. Which of the following scenarios demonstrates a biased sample? Select all that apply. A teacher needs students to come to the board to answer questions. She asks all of the students that are wearing green to come to the board. Kevin wants to determine the best shooters on his basketball team. He breaks the team into five groups and randomly selects a player from each group to shoot free throws. A store at the mall put a sign out that said, "Come in and fill out our survey for free samples!" Nicholas needs to interview people for a class project. He calls everyone in his phone contact list to ask them a series of three questions.

In statistical terms, a biased sample occurs when certain members of a population are more likely to be selected than others, which can skew the results of a study or survey. In these scenarios, both the teacher's method of selecting students based solely on their clothing color and Nicholas’s approach of calling only his phone contacts lead to biased samples. The teacher may only represent students who own green clothes, while Nicholas's sample is limited to people he personally knows, ignoring broader perspectives. In practice, biased samples can lead to unrepresentative data and flawed conclusions. For example, if the store's survey only attracts customers already interested in free samples, their feedback won’t reflect the views of the store’s entire customer base. When gathering data, it's crucial to ensure that the sample represents the population you're studying to yield reliable and generalizable results.