Question

Part: \( 1 / 5 \) Part 2 of 5 Find the critical values. Round the answer to three decimal places. For \( \alpha=0.10 \), the critical value is 1.282 . For \( \alpha=0.01 \), the critical value is 2.326 .

Ask by Ward Ortiz. in the United States
Feb 19,2025

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Answer

The critical values are: - For \( \alpha = 0.10 \): \( z = 1.282 \) - For \( \alpha = 0.01 \): \( z = 2.326 \)

Solution

To find the critical values for a given significance level \( \alpha \), we typically refer to the standard normal distribution (Z-distribution) table or use statistical software. The critical values correspond to the points on the Z-distribution that separate the rejection region from the non-rejection region. From the information provided: 1. For \( \alpha = 0.10 \), the critical value is \( z = 1.282 \). 2. For \( \alpha = 0.01 \), the critical value is \( z = 2.326 \). These values indicate the Z-scores that correspond to the upper tail of the normal distribution for the specified significance levels. ### Summary of Critical Values: - For \( \alpha = 0.10 \): \( z = 1.282 \) - For \( \alpha = 0.01 \): \( z = 2.326 \) Both values are already rounded to three decimal places as requested. If you need further calculations or explanations regarding how these values are derived, please let me know!

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The critical values you provided are derived from the standard normal distribution, which tells us where the tails of the distribution lie for different significance levels. For example, with an alpha level (\( \alpha \)) of 0.10, we're looking at the area in the right tail of the curve, and a critical value of 1.282 means there's a 10% chance of finding a value greater than this in a standard normal distribution. In real-life applications, these critical values come in handy when conducting hypothesis tests. If your calculated test statistic exceeds the critical value, you can reject the null hypothesis. This helps businesses make informed decisions based on statistical evidence, such as determining if a new marketing strategy significantly increases sales or if a product meets quality standards.

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