Hey there!
I have a question about the difference in results between the Shapiro Wilk test and the calculation of a Z score with skweness and kurtosis (divided by SE).
I have a sample size of N = 143. It is divided into two groups (Western candidates N = 71 and nonWestern candidates N = 72). To assess the normality, I did the following:
Calculate a zscore by dividing the values for skewness and kurtosis by their respective standard errors (SE).
If I use this calculation, I only have 1 nonnormal distribution. However, when I look at the Shapiro wilk test of normality within the output, all analyzes are NOT normally distributed (except one). So what confuses me is that If I take a look at the normal QQ Plots, I only see an obvious nonnormality in the applicant trait importance rating for the nonWestern candidate (just as I found in the , z value calculation of the skewness and kurtosis).
Basically, the only thing I need to know is in which cases I have violated the assumption of normality (according to Zvalues and QQ plots only in 1 case, while according to Shapiro Wilk in 5 cases).
In my thesis I wrote the following about this: (this is the part I have doubts about whether I have used the correct method):
Various methods for normality testing were used to assess whether the applicant rating scores for each level of the candidate (Western and nonWestern) were normally distributed. To assess normality within the total sample (N = > 50), Normal QQ Plots were visually inspected, and zscores were calculated by dividing the skewness and kurtosis values by their respective standard errors. Mayers (2013) suggested that a cutoff of ±2.58 should be used for samples from 51 to 100 participants. Applicant rating scores for each level of the candidate (Western and nonWestern) were normally distributed, except for the applicant trait importance rating of the nonWestern applicants with a skewness of .92 (SE = .28) and kurtosis of 1.68 (SE = .56).
So I only want to know whether I should write down the results like I did in the paragraph above. OR that I should say something like:
Within the total sample, all applicant rating scores for each level of the candidate (Western and nonWestern) violated the assumption of normality, as assessed by ShapiroWilk’s test (p < .05), except for the credential rating of the nonWestern candidate.
That's all I want to know. Thanks!
I will attach the screenshots of the QQ plots and also the Shapiro Wilk outcome and the Skewness and Kurtosis numbers.
I have a question about the difference in results between the Shapiro Wilk test and the calculation of a Z score with skweness and kurtosis (divided by SE).
I have a sample size of N = 143. It is divided into two groups (Western candidates N = 71 and nonWestern candidates N = 72). To assess the normality, I did the following:
Calculate a zscore by dividing the values for skewness and kurtosis by their respective standard errors (SE).
If I use this calculation, I only have 1 nonnormal distribution. However, when I look at the Shapiro wilk test of normality within the output, all analyzes are NOT normally distributed (except one). So what confuses me is that If I take a look at the normal QQ Plots, I only see an obvious nonnormality in the applicant trait importance rating for the nonWestern candidate (just as I found in the , z value calculation of the skewness and kurtosis).
Basically, the only thing I need to know is in which cases I have violated the assumption of normality (according to Zvalues and QQ plots only in 1 case, while according to Shapiro Wilk in 5 cases).
In my thesis I wrote the following about this: (this is the part I have doubts about whether I have used the correct method):
Various methods for normality testing were used to assess whether the applicant rating scores for each level of the candidate (Western and nonWestern) were normally distributed. To assess normality within the total sample (N = > 50), Normal QQ Plots were visually inspected, and zscores were calculated by dividing the skewness and kurtosis values by their respective standard errors. Mayers (2013) suggested that a cutoff of ±2.58 should be used for samples from 51 to 100 participants. Applicant rating scores for each level of the candidate (Western and nonWestern) were normally distributed, except for the applicant trait importance rating of the nonWestern applicants with a skewness of .92 (SE = .28) and kurtosis of 1.68 (SE = .56).
So I only want to know whether I should write down the results like I did in the paragraph above. OR that I should say something like:
Within the total sample, all applicant rating scores for each level of the candidate (Western and nonWestern) violated the assumption of normality, as assessed by ShapiroWilk’s test (p < .05), except for the credential rating of the nonWestern candidate.
That's all I want to know. Thanks!
I will attach the screenshots of the QQ plots and also the Shapiro Wilk outcome and the Skewness and Kurtosis numbers.
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