A jury must determine the guilt of a criminal defendant (not guilty, guilty). Identify how the jury would make a correct decision. Analyze how the jury would commit a Type I error versus a Type II error.
[In the present justice system an individual is innocent until a proven guilty protocol (the null hypothesis). If the jury commit a Type I error when finding if a defendant is innocent or guilty, they are not accepting (rejecting) the fact that the defendant is innocent hence they are not accepting the null hypothesis and an innocent person will be sentenced for a crime they did not commit. The same is right in Type II errors if the jury accepts the null hypothesis (innocence) then there are chances that a criminal will be set free.]
An I/O psychologist asks employees to complete surveys measuring job satisfaction and organizational citizenship behavior. She intends to measure the strength of association between these two variables. The researcher is concerned that she will commit a Type I error. What research decision influences the magnitude of risk of a Type I error in her study?
[In the given study, the psychologist measures the strength of association between the two variables, measuring job satisfaction and organizational citizenship behavior. Moreover, the researcher is concerned that she would make a Type I error. That is, rejecting the null hypothesis when it is true.
The critical region of the test is denoted by alpha which, represents the level of significance. Also, for any research study, it is difficult to avoid Type I error. Hence, the significance level is fixed for any test that is performed. This Type I error can be reduced when the sample size increases.
In other words, as the sample size increases the extent of Type I error can be reduced. This is because when the sample size is increased, there are more subjects to represent the population.
Hence, it can be concluded that the sample size that is selected for the study influences the magnitude of risk for a Type I error.]
A clinical psychologist is studying the efficacy of a new drug medication for depression. The study includes a placebo group (no medication) versus a treatment group (new medication). He then measures the differences in depressive symptoms across the two groups.
What would a Type I error represent within the context of his study? How can he reduce the risk of committing a Type I error? How does this decision affect the risk of committing a Type II error?
[A clinical psychologist is examining the viability of another medication prescription for depression. The investigation incorporates a placebo/fake treatment gathering versus a treatment gathering. The psychologist estimates the distinctions in depressive indications over the two gatherings and or groups.
What might a Type I error speak to inside the setting of his investigation? How might he diminish the danger of submitting a Type I error? How does this choice influence the danger of conferring a Type II error? A Type I error would speak to the dismissal that the new medication has turned out to be effective for depression treatment, while a Type II error would propose that the new medication has demonstrated ineffective for depression. The danger of submitting a Type I error can be decreased by expanding the example measure. The use of a substantial example or gathering will set a low alpha level and reduction odds of making a Type II error.]
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