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Author Question: A researcher reports r = .60, p =.02 when correlating the relationship between anxiety level and ... (Read 79 times)

neverstopbelieb

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A researcher reports r = .60, p =.02 when correlating the relationship between anxiety level and pulse rate in a study with an alpha of .05. How should the nurse who is reading this report interpret these results?
 
  1. As anxiety increased, so did pulse rates in this study; this was a statistically significant although moderate, positive correlation.
  2. As anxiety increased, so did pulse rates in this study and this correlation was both negative and strong.
  3. As anxiety increased, so did pulse rates in this study and this correlation was a strong, positive correlation that failed to reach significance.
  4. Anxiety and pulse rates increased but the correlation was weak.

Question 2

Quantitative researchers are more likely than qualitative researchers to pursue research with prediction and control as a purpose.
 
  A) True
  B) False



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chreslie

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Answer to Question 1

1
Rationale 1: You are correct in concluding that r = .60 is a positive correlation; if the variable of anxiety increased, there was also likely to be a rise in pulse in many cases. An r of .60 is considered to be a moderate correlation and a p value of .02 is less than the preset of .05, so the difference is statistically significant.
Rationale 2: A negative correlation means that one variable increased and the other decreased. This is usually denoted by a negative (-) sign in front of the value reported.
Rationale 3: An r = .60 is positive, meaning if one variable increased the other was also likely to increase. This value also indicates a moderate correlation; so although it did not happen in all cases, the tendency for both to increase together would still be visible if you were to plot the relationship out on a scatter plot. The p value is less than , so the difference did reach significance.
Rationale 4: Correlations of .30 or less are usually considered weak, although one should remember that you can have a weak yet statistically significant correlation; the two factors are not mutually exclusive.

Answer to Question 2

A





 

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