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Sign test:
- Non-parametric data (Nominal)
- Repeated measures or Matched pairs
- Test of difference
1. Add all pluses and minuses, S = whichever is lower (excluding 0 scoring pps)
2. N = total number of pps (excluding 0 scoring ones)
3. Find the tail test and level of significance and N to see the critical value
4. To be significant, the S must be equal to or less than the critical value
4. If it is higher, it is not significant, and we must accept the null hypothesis
Mann-Whitney test:
- Non-parametric data (Ordinal)
- Independent groups
- Test of difference
Wilcoxon test:
- Non-parametric data (Ordinal)
- Repeated measures or matched pairs
- Test of difference
Unrelated t-test:
- Interval data
- Repeated measures
- Test of difference
1. Find df (Na + Nb - 2)
2. Is it one or two tailed, what's the degree of significance?
3. That is the CV (calculated value), is it greater than or less than the S
4. Reject or accept the null hypothesis
Related t-test:
- Parametric data (interval or ratio)
- Repeated measures or matched pairs
- Test of difference
1. Find df (N-1)
2. Is it one or two tailed, what's the degree of significance?
3. That is the CV (calculated value), is it greater than or less than the S
4. Reject or accept the null hypothesis
Spearman rho test:
Pearson test:
- Parametric data (interval or ratio)
- Test of correlation
1. Find df (N-2)
2. Is it one or two tailed, what's the degree of significance?
3. That is the CV (calculated value), is it greater than or less than the S
4. Reject or accept the null hypothesis
Chi-squared test:
- Non-parametric data (Nominal)
- Independent groups
- Test of difference
1. Find df (no. of rows-1)x(no. of columns-1)
2. Is it one or two tailed, what's the degree of significance?
3. That is the CV (calculated value), is it greater than or less than the S
4. Reject or accept the null hypothesis