Analyzing Employee Satisfaction Survey Results
When you collect employee satisfaction survey results, you are often working with data based on Likert scales. A Likert scale is a common method for measuring attitudes or opinions, typically ranging from "strongly disagree" to "strongly agree" or from "very dissatisfied" to "very satisfied." In HR surveys, you might see questions like "How satisfied are you with your current role?" with responses on a 1-5 scale, where 1 means "very dissatisfied" and 5 means "very satisfied." Summarizing these responses helps you quickly understand how employees feel about different aspects of their work environment and identify areas for improvement.
123responses = [4, 5, 3, 4, 2, 5, 4, 3, 5, 4] # Example Likert scale responses (1-5) average_score = sum(responses) / len(responses) print("Average satisfaction score:", average_score)
Interpreting the average satisfaction score can reveal overall employee sentiment. For instance, an average score close to 5 suggests high satisfaction, while a score near 1 signals widespread dissatisfaction. Tracking these scores over time or comparing them across departments can help you identify positive trends or areas needing attention.
12345responses = ["satisfied", "unsatisfied", "satisfied", "satisfied", "unsatisfied", "satisfied"] num_satisfied = responses.count("satisfied") num_unsatisfied = responses.count("unsatisfied") print("Number of satisfied responses:", num_satisfied) print("Number of unsatisfied responses:", num_unsatisfied)
1. What is a Likert scale commonly used for in HR surveys?
2. How can Python help summarize survey results?
3. Fill in the blank: To count occurrences of a value in a list, use the _______ method.
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When you collect employee satisfaction survey results, you are often working with data based on Likert scales. A Likert scale is a common method for measuring attitudes or opinions, typically ranging from "strongly disagree" to "strongly agree" or from "very dissatisfied" to "very satisfied." In HR surveys, you might see questions like "How satisfied are you with your current role?" with responses on a 1-5 scale, where 1 means "very dissatisfied" and 5 means "very satisfied." Summarizing these responses helps you quickly understand how employees feel about different aspects of their work environment and identify areas for improvement.
123responses = [4, 5, 3, 4, 2, 5, 4, 3, 5, 4] # Example Likert scale responses (1-5) average_score = sum(responses) / len(responses) print("Average satisfaction score:", average_score)
Interpreting the average satisfaction score can reveal overall employee sentiment. For instance, an average score close to 5 suggests high satisfaction, while a score near 1 signals widespread dissatisfaction. Tracking these scores over time or comparing them across departments can help you identify positive trends or areas needing attention.
12345responses = ["satisfied", "unsatisfied", "satisfied", "satisfied", "unsatisfied", "satisfied"] num_satisfied = responses.count("satisfied") num_unsatisfied = responses.count("unsatisfied") print("Number of satisfied responses:", num_satisfied) print("Number of unsatisfied responses:", num_unsatisfied)
1. What is a Likert scale commonly used for in HR surveys?
2. How can Python help summarize survey results?
3. Fill in the blank: To count occurrences of a value in a list, use the _______ method.
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