Final answer:
The risks related to testing effectiveness are Type I error, which is the risk of incorrect rejection and corresponds to option 1, and Type II error, which is the risk of incorrect acceptance and aligns with option 3.
Step-by-step explanation:
Risks Related to the Effectiveness of Testing
The risks related to the effectiveness of testing within the scenario of hypothesis testing in statistics are the Type I and Type II errors. A Type I error occurs when a true null hypothesis is incorrectly rejected, which corresponds to option 1) The risk of incorrect rejection. A Type II error happens when a false null hypothesis is incorrectly accepted as true, which aligns with option 3) The risk of incorrect acceptance.
To illustrate, consider a scenario where we have the null hypothesis that the percentage of adults who have jobs is at least 88 percent. A Type I error would be to reject this null hypothesis when, in fact, it is true (the percentage of adults with jobs is indeed at least 88 percent). Conversely, a Type II error would be not to reject the null hypothesis when, in fact, it is false (the percentage of adults with jobs is less than 88 percent).