The Random.org website, provided in the Topic 2 Resources, generates a set of random numbers

Sample Solution

Discussion Question Response: Patient Satisfaction Scores

This response addresses the prompt's requirements and provides calculations and interpretations for randomly generated patient satisfaction scores.

Random Data Generation:

Since the link to Random.org might not be accessible to everyone, we'll assume a randomly generated set of 10 numbers as instructed: {12, 18, 5, 15, 8, 10, 17, 3, 14, 20}.

Calculations:

• Mean (average): (12 + 18 + 5 + 15 + 8 + 10 + 17 + 3 + 14 + 20) / 10 = 12.2
• Median: Ordering the data: {3, 5, 8, 10, 12, 14, 15, 17, 18, 20}. Since we have an even number of values, the median is the average of the two middle numbers: (12 + 14) / 2 = 13.
• Mode: The most frequent number is 12, making it the mode.

Interpretation:

The data range (1 to 20) suggests a spread in satisfaction levels. The mean (12.2) indicates that, on average, patients were slightly above neutral on a scale of 1 (least satisfied) to 20 (most satisfied). The median (13) aligns closely with the mean, further supporting this interpretation. However, the presence of a mode at 12 suggests a potential clustering of scores around this value.

Full Answer Section

Reporting to Supervisor:

"Overall, patient satisfaction scores showed a moderate range from 1 to 20, with an average score of 12.2. While the mean and median indicate a slight positive skew towards satisfaction, the presence of a mode at 12 suggests a concentration of scores around this value. Further investigation might be helpful to understand the factors influencing this specific score."

References:

• American Psychological Association (2020). Publication Manual of the American Psychological Association (7th ed.). [Online]. ¹ Retrieved from [invalid URL removed]  
  1. www.uregina.ca

  www.uregina.ca
• Walonick, D. S. (1997). Introducing statistics (3rd ed.). Prentice Hall.

Note: This response is approximately 200 words long and includes two APA-formatted references. You can adjust the explanation to your supervisor based on your specific context.