COM CM 321 Lecture Notes - Lecture 10: Type I And Type Ii Errors, Null Hypothesis, Contingency Table

• School: Boston University
• Department: Mass Communication, Advertising & Public Relations
• Course: COM CM 321
• Professor: Yiyan Zhang

Document Summary

Hypothesis: a statement about the relationship between independent and dependent variables. Hypothesis testing: testing the significance level of a hypothesis: whether the relationship(s) we find in the study is by chance/due to random error, whether we can reject the null hypothesis. Null hypothesis: a little bit different in this context, assuming no real difference, the logical alternative to your original rq/h, original hypothesis: h1, null hypothesis: h0, if we reject h0, we accept h1. Needs to be put into the theoretical background (the difference between a statistically significant result and a meaningful result: there are still chances that we are reaching a conclusion by mistake, address type i and type ii errors. Type i and type ii errors: type i error: false positive; claimed to exist but does not exist, type ii error: false negative; claimed to not exist but does exist. If they are due to random errors, we cannot control.