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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 6.1.8

In Exercises 5–8, find the critical value zc necessary to construct a confidence interval at the level of confidence c.
c = 0.97

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Step 1: Understand the problem. The goal is to find the critical value (zc) for a confidence interval at a given confidence level (c = 0.97). The critical value corresponds to the z-score that separates the middle 97% of the standard normal distribution from the remaining 3%.
Step 2: Recall that the confidence level (c) represents the proportion of the area under the standard normal curve that is within the confidence interval. For c = 0.97, the remaining area outside the interval is 1 - c = 0.03, which is split equally between the two tails of the distribution.
Step 3: Calculate the area in one tail. Since the total area outside the confidence interval is 0.03, the area in one tail is 0.03 / 2 = 0.015.
Step 4: Determine the cumulative area to the left of the critical value zc. The cumulative area includes the area in the left tail (0.015) and the middle area (0.97). Therefore, the cumulative area is 0.015 + 0.97 = 0.985.
Step 5: Use a standard normal table or a statistical software to find the z-score (zc) corresponding to a cumulative area of 0.985. This z-score is the critical value zc needed for the confidence interval.

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Critical Value (zc)

The critical value, denoted as zc, is a point on the standard normal distribution that corresponds to a specified level of confidence. It is used to determine the margin of error in constructing confidence intervals. For a given confidence level, zc represents the number of standard deviations away from the mean that captures the desired percentage of the data.
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Critical Values: t-Distribution

Confidence Level

The confidence level, often expressed as a percentage (e.g., 97%), indicates the degree of certainty that the population parameter lies within the confidence interval. A higher confidence level means a wider interval, reflecting greater uncertainty about the exact value of the parameter. It is crucial for determining the critical value and the overall reliability of the interval estimate.
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Introduction to Confidence Intervals

Standard Normal Distribution

The standard normal distribution is a probability distribution that has a mean of 0 and a standard deviation of 1. It is used as a reference for calculating probabilities and critical values in statistics. When constructing confidence intervals, the z-scores derived from this distribution help identify the critical values needed for the specified confidence level.
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Finding Standard Normal Probabilities using z-Table
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