Descriptive Statistics for Analyzing Quantitative Data

You are in charge of the HR Department for your agency and one of your primary responsibilities is to recruit and interview applicants. You heard from a colleague in a comparable position at another agency that they use an instrument that has been very helpful with this task called the UPickdM Test. You decide to try the Test and administer it to the next 10 applicants you see. The Test assigns scores based on ratings of performance on several role-playing exercises by a highly qualified judge with several years of experience. Your applicants all take the Test, and their scores are shown below. Since this is your first experience with the UPickdM Test you do not know if these scores are relatively high or low, so you ask your colleague in the comparable agency if you could have the scores on the same test of ten individuals who are model employees. That way, you could see if your applicants compare with the high scoring ones in the other agency and make your hiring choices based on these results.

UPickdM Test Scores for:

Your Applicants Other Agencyâs Employees

      61                                                                                                        78

      51                                                                                                        83

      73                                                                                                        81

      42                                                                                                        66

      91                                                                                                        81

      80                                                                                                        89

      77                                                                                                        85

      73                                                                                                        79

      64                                                                                                        71

      88                                                                                                        77

Calculate the measures of central tendency for the two groups.
Which measure of central tendency do you think is the best one to use to give a picture of the average participant in each group? (your response does not have to be the same for both groups)
Calculate the measures of variability for the two groups.
Which measure of variability do you think is the best one to use to give a picture of the average participant in each group? (your response does not have to be the same for both groups)
Now compare the mean and variance for both groups. What does this tell you?

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Sample Answer

 

 

 

 

Calculate the measures of central tendency for the two groups.

Your Applicants:

  • Mean: (61 + 51 + 73 + 42 + 91 + 80 + 77 + 73 + 64 + 88) / 10 = 700 / 10 = 70
  • Median: First, order the scores: 42, 51, 61, 64, 73, 73, 77, 80, 88, 91. The median is the average of the two middle scores: (73 + 73) / 2 = 73
  • Mode: The score that appears most frequently is 73 (appears twice).

Other Agency’s Employees:

  • Mean: (78 + 83 + 81 + 66 + 81 + 89 + 85 + 79 + 71 + 77) / 10 = 790 / 10 = 79
  • Median: First, order the scores: 66, 71, 77, 78, 79, 81, 81, 83, 85, 89. The median is the average of the two middle scores: (79 + 81) / 2 = 80
  • Mode: The score that appears most frequently is 81 (appears twice).

2. Which measure of central tendency do you think is the best one to use to give a picture of the average participant in each group? (your response does not have to be the same for both groups)

  • Your Applicants: The median (73) might be the best measure of central tendency for your applicants. The mean (70) is slightly pulled down by the lower scores (42 and 51), which might not be truly representative of the “typical” applicant. The median is less sensitive to extreme values.

  • Other Agency’s Employees: The mean (79) and the median (80) are quite close for the other agency’s employees. In this case, the mean (79) could be considered a good representation of the average model employee’s score, as the scores are relatively clustered without extreme outliers significantly skewing the average.

3. Calculate the measures of variability for the two groups.

Your Applicants:

  • Range: Highest score (91) – Lowest score (42) = 49

Full Answer Section

 

 

 

 

  • Variance (Sample):
    1. Deviations from the mean (70): -9, -19, 3, -28, 21, 10, 7, 3, -6, 18
    2. Squared deviations: 81, 361, 9, 784, 441, 100, 49, 9, 36, 324
    3. Sum of squared deviations: 81 + 361 + 9 + 784 + 441 + 100 + 49 + 9 + 36 + 324 = 2194
    4. Variance (s²): 2194 / (10 – 1) = 2194 / 9 = 243.78 (approximately)
  • Standard Deviation (Sample): √243.78 = 15.61 (approximately)

Other Agency’s Employees:

  • Range: Highest score (89) – Lowest score (66) = 23
  • Variance (Sample):
    1. Deviations from the mean (79): -1, 4, 2, -13, 2, 10, 6, 0, -8, -2
    2. Squared deviations: 1, 16, 4, 169, 4, 100, 36, 0, 64, 4
    3. Sum of squared deviations: 1 + 16 + 4 + 169 + 4 + 100 + 36 + 0 + 64 + 4 = 400
    4. Variance (s²): 400 / (10 – 1) = 400 / 9 = 44.44 (approximately)
  • Standard Deviation (Sample): √44.44 = 6.67 (approximately)

4. Which measure of variability do you think is the best one to use to give a picture of the average participant in each group? (your response does not have to be the same for both groups)

  • Your Applicants: The standard deviation (15.61) is likely the best measure of variability for your applicants. It provides a sense of the typical spread of scores around the mean. The range (49) is informative but only considers the extreme values and doesn’t tell us about the distribution of the scores in between.

  • Other Agency’s Employees: Similarly, the standard deviation (6.67) is the best measure of variability for the other agency’s employees. It shows that their scores are much more tightly clustered around their mean compared to your applicants.

5. Now compare the mean and variance for both groups. What does this tell you?

Comparing the mean and variance for both groups reveals the following:

  • Mean Comparison: The mean score for the other agency’s model employees (79) is higher than the mean score for your applicants (70). This suggests that, on average, the model employees in the other agency performed better on the UPickdM Test than your applicant pool.

  • Variance Comparison: The variance for your applicants (243.78) is significantly higher than the variance for the other agency’s employees (44.44). This indicates that there is much greater variability in the UPickdM Test scores among your applicants. Some scored quite low, while others scored quite high. In contrast, the scores of the model employees in the other agency are much more consistent and clustered closer to their mean.

What this tells you for hiring:

The results suggest that, as a group, your applicants did not perform as well on the UPickdM Test as the model employees in the other agency. However, the high variance among your applicants indicates that there are some individuals within your applicant pool who scored comparably to or even higher than some of the model employees (e.g., the applicant with a score of 91).

Therefore, relying solely on the mean comparison might lead you to overlook potentially strong candidates within your applicant pool. The higher variance highlights the importance of looking at individual scores rather than just the group average. You have some applicants who performed very well on this test, and they might be worth serious consideration alongside other factors in your hiring process. Conversely, the lower variance in the model employee group suggests a more consistent level of high performance on this particular test.

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