Read the scenario and answer the questions below:

A researcher reports that there was a highly significant difference in two groups because the analysis was significant with aPvalue <.001.

1. Explain the finding in terms of likelihood or probability.

2. How does the report fit with decision theory?

3. Which result has a greater risk of type II error: aPvalue of .0001 orPvalue of .001?

Read the following scenario and answer the question below:

Before the study, researchers calculated that a total sample size of 134 subjects was needed for a power of 0.8. During the study, researchers only achieved a sample size of 84 subjects.

1. With an inadequate sample size, there is an increased risk of what type of error?

Read the scenarios and answer the questions below:

1. A researcher predicts that as anxiety increases, chest pain increases. What type of relationship is predicted between the variables?
2. A report of a cross-sectional study of postoperative patients contains the finding of a significant correlation between pain and immobility. The report concludes that postoperative pain causes immobility. What is your appraisal of this conclusion?
3. A researcher reports that the correlation between the mean scores of two instruments isr= 0.48. Was the relationship significant?
4. What is the relationship between the total spiritual score and the total social support score in the hypothetical data file?
5. A correlation ofr =0.34 was found between pain and immobility. What percentage of the variance is explained? What percentage is unexplained?

Answer the questions below:

1. What is another name forR²when more than one independent variable is used to predict the dependent variable?
2. Which statistical procedure could be used to predict the total coping (dependent variable) by including the independent variables of spirituality and social support?

Read the scenario and answer the questions below:

A group of researchers conducted a power analysisbefore conducting a study comparing two types of patient teaching for multiple sclerosis: usual teaching and a computerized learning game. The dependent variable was perceived self-efficacy in managing medication side effects. The power analysis revealed that 45 subjects were needed in both groups for a power of 0.8 at a significance level of .05. The researchers randomly assigned 47 persons to each group. The study attrition was 10% for both groups. No significant differences were found between groups in perceived self-efficacy.

1. What is your appraisal of these findings?

2. What factors may have contributed to the insignificant results?

3. What additional information do you need to appraise these findings?