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g PROBLEM 3. Based on data from Consumer Reports, replacement times of TVs is on average 3.75 years with the standard deviation of 2.5 years. Answer the following questions. Question 1 (3 points). A random sample of 28 TVs is chosen. What is the probability that their average replacement time is less than 3.5 years

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Answer:

29.81% probability that their average replacement time is less than 3.5 years

Explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal probability distribution

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean
\mu and standard deviation
\sigma, the zscore of a measure X is given by:


Z = (X - \mu)/(\sigma)

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean
\mu and standard deviation
\sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
\mu and standard deviation
s = (\sigma)/(√(n)).

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

In this problem, we have that:


\mu = 3.75, \sigma = 2.5, n = 28, s = (2.5)/(√(28)) = 0.47

What is the probability that their average replacement time is less than 3.5 years

This is the pvalue of Z when X = 3.5. So


Z = (X - \mu)/(\sigma)

By the Central Limit Theorem


Z = (X - \mu)/(s)


Z = (3.5 - 3.75)/(0.45)


Z = -0.53


Z = -0.53 has a pvalue of 0.2981

29.81% probability that their average replacement time is less than 3.5 years

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