(a) Spearman’s Rank Correlation Coefficient is a suitable measure of correlation in the following situations:

• When at least one of the variables is measured on an ordinal scale (ranked data), as is the case here with interview rankings.
• When the data does not meet the assumptions required for Pearson’s correlation, such as normality of distribution or linearity of relationship.
• When the relationship between variables is monotonic (consistently increasing or decreasing) but not necessarily linear.
• When there are outliers in the data that could distort parametric measures like Pearson’s coefficient.
• As a non-parametric alternative to assess the strength and direction of association between two variables without assuming a specific distribution.

In the context of banking personnel assessment, Spearman’s is particularly useful for correlating quantitative scores (like aptitude) with subjective rankings (like interview performance), ensuring robust analysis compliant with data-driven HR decisions in Ghanaian banks, aligning with BoG’s emphasis on fair and objective recruitment practices.

(b) Given that the interview data is in rankings (ordinal), Spearman’s Rank Correlation Coefficient is the suitable measure.

To calculate it:

1. Rank the aptitude scores in ascending order (lowest score gets rank 1, highest gets rank 10):

• E (14): 1
• F (33): 2
• A (38): 3
• D (40): 4
• B (59): 5
• I (62): 6
• C (68): 7
• H (71): 8
• J (81): 9
• G (87): 10

2. The interview rankings are given, with a tie at rank 3 for H and I. To handle the tie, assign the average rank: (3 + 4)/2 = 3.5 to both H and I. The adjusted ranks (ascending order of ranking values) are implicit in the calculation.

Interview ranks (as given, but adjusted for tie):

• F: 1
• G: 2
• H: 3.5
• I: 3.5
• B: 5
• J: 6
• D: 7
• C: 8
• E: 9
• A: 10

3. Now, pair the ranks and calculate differences (d = aptitude rank – interview rank) and d²:

Sum of d² = 49 + 0 + 1 + 9 + 64 + 1 + 64 + 20.25 + 6.25 + 9 = 223.5

4. Spearman’s rho (ρ) = 1 – [6 × Σd² / n(n² – 1)], where n = 10

   = 1 – [6 × 223.5 / (10 × (100 – 1))] = 1 – [1341 / (10 × 99)] = 1 – [1341 / 990] = 1 – 1.3545 ≈ -0.3545

(Note: This is an approximation; the exact value using Pearson’s correlation on ranks is approximately -0.359, accounting for ties more precisely.)

(c) The calculated Spearman’s rank correlation coefficient of approximately -0.36 indicates a moderate negative correlation between aptitude scores and interview rankings. This suggests that higher aptitude scores tend to be associated with lower (better) interview ranking numbers, implying that employees with stronger aptitude generally perform better in interviews. However, the strength is moderate, meaning the relationship is not very strong, and other factors (e.g., communication skills, experience) may influence interview outcomes. In a banking context, this could inform HR strategies at Mumuadu Community Bank, such as weighting aptitude tests more in initial screening while ensuring compliance with fair hiring practices under Ghanaian labor laws and BoG guidelines on corporate governance. The presence of outliers (e.g., Employee F with low aptitude but top interview rank) may weaken the correlation, highlighting the need for multifaceted assessment tools.