Author Question: Which of the following should a reader of a research article be able to do, in order to decide ... (Read 51 times)

Metfan725 · **on:** Jul 8, 2018

Which of the following should a reader of a research article be able to do, in order to decide whether the article's statistics are correctly selected and applied? (Select all that apply.)

a. Understand the discussion section of the article.
b. Make a judgment as to whether the author's interpretations of the data are correct.
c. Make some judgment about whether the statistical procedures used were the correct ones for the level of measurement used for the study variables.
d. Make some judgment about whether the statistical procedures used were the correct ones for the research question.
e. Agree with the study's stated limitations.
f. Find the names of the statistical procedures the author used.

Question 2

Why can type I error and type II error not be both present for one given hypothesis?

a. Power analysis makes one type of error less likely.
b. One refers to rejecting the null hypothesis when it is true and the other to accepting it when it is false.
c. As beta rises, alpha falls.
d. The researcher sets both the alpha level and the beta level.
e. Qualitative research does not use power analysis.

djpooyouma · **Reply #1 on:** Jul 8, 2018

Answer to Question 1

ANS: A, B, C, D, F
To critically appraise the results section of a quantitative study, the reader needs to be able to (1) identify the statistical procedures used, (2) judge whether these statistical procedures were appropriate for the hypotheses, questions, or objectives of the study and for the data available for analysis, (3) comprehend the discussion of data analysis results, (4) judge whether the author's interpretation of the results is appropriate, and (5) evaluate the clinical importance of the findings.

Answer to Question 2

ANS: B, C
The researcher sets the values of two theoretical probabilities: (1) the probability of rejecting the null hypothesis when it is in fact true (alpha ; type I error), and (2) the probability of retaining the null hypothesis when it is in fact false (beta ; type II error). In nursing research, alpha is usually set at 0.05, meaning that the researcher will allow a 5 or lower chance of making a type I error. The beta is frequently set to 0.20, meaning that the researcher will allow for a 20 or lower chance of making a type II error. A type II error occurs if the null hypothesis is regarded as true when, in fact, it is false.