When σ is unknown and the sample size is n\geq30, there are tow methods for computing confidence intervals for μμ. Method 1: Use the Student's t distr

nagasenaz

nagasenaz

Answered question

2021-05-14

When σ is unknown and the sample size is n30, there are tow methods for computing confidence intervals for μμ. Method 1: Use the Student's t distribution with d.f. = n - 1. This is the method used in the text. It is widely employed in statistical studies. Also, most statistical software packages use this method. Method 2: When n30, use the sample standard deviation s as an estimate for σσ, and then use the standard normal distribution. This method is based on the fact that for large samples, s is a fairly good approximation for σσ. Also, for large n, the critical values for the Student's t distribution approach those of the standard normal distribution. Consider a random sample of size n = 31, with sample mean x¯=45.2 and sample standard deviation s = 5.3. (c) Compare intervals for the two methods. Would you say that confidence intervals using a Student's t distribution are more conservative in the sense that they tend to be longer than intervals based on the standard normal distribution?

Answer & Explanation

d2saint0

d2saint0

Skilled2021-05-15Added 89 answers

90%: 43.5846 to 46.8154 for result component (a).
95%: 43.2562 to 47.1438\s99%: 42.5823 to 47.8177
90%: 43.6341 to 46.7659 95%: 43.3343 to 47.0657 Result section (b)
99%: 42.7441 to 47.6559
Because they are a little broader than those based on the conventional normal distribution, the confidence intervals utilizing a Student's t distribution are more circumspect.

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