Statistical Inference
10 videos • 119 views • by Fourth Z This is Playlist 6 in the Introduction to Behavioral and Social Statistics series. Statistical inference is about making inferences in two ways. First, if we have randomly sampled from our population, we can use inferential methods to make claims about the larger population, and to do so with confidence. Second, if we have conducted a true experiment in which we randomized to conditions, we can use inference to ascertain that potential cause-effect relationships are indeed causal relationships, and not just an artifact of our randomization. We make these inferences using a powerful statistical tool known as a confidence interval. First, however, we need to learn an older method known as hypothesis testing, as this forms the basis for constructing confidence intervals. We also need to know about hypothesis testing because so much past research is based on these tests, and some researchers continue to use this method. Finally, because inferential statistics are so easy to misuse, we need to consider some of the major issues about inference so as to avoid misuse. The anticipated learning outcomes for this playlist are these: 1. You can explain the difference in using statistics for description and inference. 2. You can describe the roles of inference in resesarch. 3. You can describe the steps of hypothesis testing. 4. You can describe the steps for constructing a confidence interval. 5. You can compare and contrast Type I and Type II errors. 6. You can interpret a p-value. 7. You can determine if a sample came from a known population. 8. You can construct a confidence interval for the population mean that is represented by a sample from an unknown population. 9. You can describe the limitations of statistical inference.