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Ch. 6 - Confidence Intervals
Larson - Elementary Statistics: Picturing the World 8th Edition
Larson8th EditionElementary Statistics: Picturing the WorldISBN: 9780137493470Non è quello che usi tu?Cambia libro di testo
Capitolo 6, Problema 6.1.16

In Exercises 13–16, find the margin of error for the values of c, σ and n.
c = 0.975, σ = 4.6, n = 100

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Step 1: Understand the formula for the margin of error (ME). The formula is ME = Z * (σ / √n), where Z is the critical value corresponding to the confidence level (c), σ is the population standard deviation, and n is the sample size.
Step 2: Determine the critical value (Z) for the given confidence level (c = 0.975). Use a Z-table or statistical software to find the Z-value that corresponds to the middle 97.5% of the standard normal distribution.
Step 3: Calculate the standard error (SE) using the formula SE = σ / √n. Substitute the given values of σ = 4.6 and n = 100 into the formula.
Step 4: Multiply the critical value (Z) by the standard error (SE) to compute the margin of error (ME). This step combines the results from Step 2 and Step 3.
Step 5: Interpret the margin of error in the context of the problem. The margin of error represents the range within which the true population parameter is expected to lie with the given confidence level.

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Margin of Error

The margin of error quantifies the uncertainty in a sample estimate. It indicates the range within which the true population parameter is expected to lie, given a certain confidence level. A smaller margin of error suggests a more precise estimate, while a larger margin indicates more variability. It is commonly used in survey results and statistical inference.
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Finding the Minimum Sample Size Needed for a Confidence Interval

Confidence Level (c)

The confidence level represents the probability that the margin of error will contain the true population parameter. In this case, a confidence level of 0.975 means that if the same sampling method were repeated multiple times, approximately 97.5% of the calculated margins of error would capture the true value. It reflects the degree of certainty in the results.
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Introduction to Confidence Intervals

Standard Deviation (σ) and Sample Size (n)

Standard deviation (σ) measures the dispersion of data points around the mean, indicating how spread out the values are. A larger standard deviation suggests more variability in the data. Sample size (n) refers to the number of observations in a sample; larger sample sizes generally lead to more reliable estimates and smaller margins of error, as they better represent the population.
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Calculating Standard Deviation