Final answer:
In a Functional Job Analysis, tasks are rated based on interactions with things, data, and people option (c). Observation, surveys, and interviews are critical methods for gathering job analysis data. The work-content factor, including variety, difficulty, and clarity, notably influences job satisfaction.
Step-by-step explanation:
In a Functional Job Analysis, tasks are evaluated based on their interaction with three factors: things, data, and people. This approach examines what a job entails and how it is performed by studying the tasks that require interaction with people, objects, and data. By rating tasks on these factors, a clearer picture of a job's requirements can be developed.
Job analysis can be performed through various methods, including observation, surveys, and interviews. Observing someone proficient in a position provides real-time data on necessary skills, while interviews with job incumbents and their supervisors offer insights into perceived job requirements.
Research on the reliability of job analysis indicates variability based on who provides job descriptions. Analyses using descriptions from current job holders may be less reliable, possibly due to subjective views influencing the accuracy.
Additionally, the work-content factor is found to be a strong predictor of job satisfaction, suggesting that the nature of work itself, including variety, difficulty, and clarity, is more impactful on satisfaction levels than financial compensation.