Question

A restaurant would like to evaluate the efficiency of its workers, so they observe the workers during the second shift.

Is this situation biased or unbiased? Explain using complete sentences.

Answer these questions in your answers: Is it representative? Why or why not?; Is it random? Why or why not?; Is the sample large enough? Why or why not?

Answer 1

The situation could be biased if the second shift is not representative of the overall workforce, lacking in randomness if all workers of the shift are observed, and potentially skewed if the sample size doesn't reflect the diversity of all shifts. More information about the selection process and workforce diversity is needed to determine bias definitively.

Step-by-step explanation:

Whether the situation described is biased or unbiased depends on several factors such as representativeness, randomness, and sample size. When evaluating the efficiency of restaurant workers observed during the second shift:

• Representativeness: If workers behave differently during different shifts and the evaluation is only for the second shift, it may not be representative of the overall efficiency of workers across all shifts.
• Randomness: If all workers on the second shift are observed, it is not a random sample of all workers. Randomness is crucial for avoiding bias in sampling.
• Sample size: The sample size should be large enough to provide reliable insights. If the second shift has fewer workers or does not depict the diversity of the entire staff, the sample size might be insufficient for an accurate assessment of worker efficiency.

In summary, without information on how the shift was chosen, how many workers it includes compared to the entire staff, and whether their pattern of work is similar to other shifts, it is difficult to confirm whether the observation leads to an unbiased assessment. The scope could be limited if behaviors during the second shift do not reflect the range of scenarios that occur in all shifts.

Answer 2

1.) It is biased

2.) No

3.) Yes

4.) No

Step-by-step explanation:

1.) It is biased as it is predisposition to one particular outcome over another.

2.) No, because biased in research leads to unrepresentative outcomes as the estimates is predisposed to the left or to the right of the true values.

3.) Yes. Since the selection of shift has an equal probability of being chosen.

4.) No. The probability that the sample accurately reflects the efficiency of the workers, the standard should be 95%.