Anton and his friends are discussing a study he read about in his developmental psychology class. In the study, the researcher m
ade the claim that most middle school students who are bullied have low self-esteem. Clarissa questions the study, saying, "I am not sure that I am convinced. I am not sure you can really measure being bullied." Quinn also questions the study, saying, "Which middle school students did they study? I am curious if they included both private and public school students." Manish also is curious about the study, asking, "I wonder how strong the relationship is between bullying and self-esteem. Could you predict one from the other?" Anton is concerned that the researcher made a Type I error. What does that mean?
The definition of Type I error is the rejection of a true null hypothesis, the type I error is also known as "False positive". Remember that a null hypothesis states that two variables are not related and that there is no association between these hypothesis. Therefore, if the Type I error rejects a true null hypothesis it means that because of this error, the findings indicate that there is actually a relation between two variables when there really isn't one.
In the case of this problem, the researcher made the claim that most middle school students that are bullied have low self-esteem. This means that<u> the researcher concluded that there's a relation between being bullied and having a low self-esteem. </u>
If Anton is concerned that the researcher made a type I error, it means that Anton thinks that the study gave some "false positives", leading the researcher to believe there's a correlation between bullying and low self-esteem when there really isn't a correlation between them.
Example: 123456 in scientific notation would be 1.23456x10^5 you rewrite the number so it is less than 10 but more than 1 and multiply it by 10 to the power of however many decimal places it takes to get the number back to its original form
