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According to the CDC, the average number of sick days workers are absent is 15 per year, with a standard deviation of 5 days. Assume a population size = 5000. From a random sample of 25 workers, what is the probability that a worker will be sick between 14 and 16 days? Make sure to calculate the appropriate standard error.

User Taha Samad
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Final answer:

To find the probability of a worker being sick between 14 and 16 days with a mean of 15 days and a standard deviation of 5 days from a sample of 25, calculate the standard error, convert the sick days to Z-scores, and use the standard normal distribution to determine the probability.

Step-by-step explanation:

The question asks for the probability that a worker will be sick between 14 and 16 days, given a population mean (μ) of 15 days and standard deviation (σ) of 5 days. To solve this, we first calculate the standard error (SE) of the sample mean by dividing the population standard deviation by the square root of the sample size, that is SE = σ / √(n), where n is the sample size. In this case, SE = 5 / √(25) = 5 / 5 = 1. Then, to find the probability that a worker will be sick between 14 and 16 days, we need to use the standard normal distribution (Z-distribution) as the sample size is large enough for the central limit theorem to come into play, although the population size is not taken into account in the calculations.

To find the Z-scores for 14 and 16 days, we use the formula Z = (X - μ) / SE. So, Z = (14 - 15) / 1 = -1 for 14 days, and Z = (16 - 15) / 1 = 1 for 16 days. We then look up these Z-values in the standard normal distribution table or use a Z-score calculator to find the probabilities corresponding to these Z-scores and subsequently calculate the probability of a worker being sick between these values.

User Kofifus
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