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Please write “true” if the statement is true and “false” is the statement is fal

ID: 3044870 • Letter: P

Question

Please write “true” if the statement is true and “false” is the statement is false in the space provided:

______ 1. A statistical hypothesis test tests the null hypothesis rather than the researcher’s hypothesis

___ ___ 2. In most research situations, the goal is to reject the researcher’s hypothesis

______ 3. A decision to reject the null hypothesis means that the data do provide evidence of a treatment effect: the independent variable did have an effect on the dependent variable

______4. If the data provide convincing evidence that the treatment does have an effect, then the correct statistical decision is to reject the null hypothesis

______5. For a hypothesis test, the critical region is defined as the set of test statistics that are very unlikely (very low probability) of being obtained if the null hypothesis is true

______ 6. If the obtained sample data (test statistic value) is inside the critical region, then we have provided support for the null hypothesis

______ 7. When the Z-test statistic, obtained from the sample data, falls inside the critical region, we reject the null hypothesis

______ 8. If the obtained sample data (test statistic value) are not in the critical region, the correct statistical decision is “fail to reject the null hypothesis.”

______ 9. If you fail to reject the null hypothesis, it means that the data provide sufficient evidence to say that the treatment has an effect: the independent variable had an effect on the dependent variable

______10. Whenever the statistical decision is to reject the null hypothesis, there is a probability that the decision is incorrect and this probability is known as Type I error

______11. The probability of committing a Type I error is equal to alpha

______12. A Type II error occurs when a treatment actually does have an effect but the effect fails to show up in a research study

______13. One way to reduce the risk of Type I error, saying there is an effect when in fact there is not an effect, is to lower the alpha level from .05 to .01

______14. Type II error is to fail to reject a null hypothesis that is actually false

______15. In a research report, the term “statistically significant” is used to indicate that the null hypothesis was rejected

______16. In a research report, the notation p< .05 is used when the null hypothesis is rejected and the IV is shown to have a significant effect using an alpha level = .05

______17. Alpha () is the probability of committing a Type II error

______18. In a Type II error, the experimenter concludes that there is evidence for an effect when in fact an effect does not exist

______19. Changing the level of significance from .01 to .05 increases the risk of Type I error

______20. When a researcher report demonstrates a significant treatment effect at the .05 alpha level, you can be more confident that the effect is real than if the researcher had reported a significant effect with an alpha level of only .01

______21. There is always a possibility that the decision in a hypothesis test is incorrect

______22.To be more confident that a treatment actually does have a real effect, a researcher should use a large value for alpha

______23. The following hypothesis: “Nicotine should increase memory ability” requires a one-tail, directional test with the entire critical region located on the right side of the distribution

______24. The following hypothesis: “Nicotine should decrease memory ability” requires a one-tail, directional test with the entire critical region located on the left side of the distribution

______25. The following hypothesis: “Nicotine will have an effect on memory” requires a two-tail, non-directional test with the critical region divided between both tails of the distribution

______26. In the following hypothesis: “Nicotine will have an effect on memory,” the dependent variable is nicotine

______27. In the following hypothesis: “Nicotine will have an effect on memory,” the independent variable is memory

______28. Researchers collect data by measuring the dependent variable in their studies

______29. Independent variables are the variables that researchers manipulate in their studies

______30. In a directional (one-tail) hypothesis test, the entire critical region is located in either one of the other tail of the distribution, but not in both tails of the distribution

______31. The reason for computing Cohen’s d is that a hypothesis test, per se, does not measure the size of the effect

______32. Cohen’s d or any other “d” measures effect size

______33. Standard error is the discrepancy or difference, on average, that you should expect between your sample mean (M) and the population mean (µ)

______34. All hypotheses tests analyze (or compare) two main differences. These differences are the differences between or among means due to the IV, and difference between or among means due to chance.

Explanation / Answer

1. True (since our aim is to reject or fail to reject the null hypothesis, and test statistic is also based on null hypothesis)

2. False ( we reject null hypothesis only with strong evidence)

3. True ( since our null hypothesis is that there is no significant effect of treatment, if the data provide enough evidence of treatment effect, we reject null hypothesis)

4. True ( as point number 3)

5. True ( that is why we reject the null hypothesis if the data point falls in the rejection region )

6. False ( if the data point in the rejection region we have evidence against null hypothesis and we reject it)

7. True ( if the test statistic is inside the rejection region we reject our null hypothesis)

8. True ( if test statistic is in rejection region, we reject the null hypothesis and if not in rejection region we fail to reject the null hypothesis)

9. False ( the null hypothesis is that there is no significant treatment effect, so if we fail to reject the null hypothesis that means there is no significant treatment effect)

10. True ( rejecting a null hypothesis when it is true is wrong decision and is known as type 1 error)