Use the given information to find the number of degrees of freedom, the critical values x and x, and the confidence interval estimate of a. It is reasonable to assume that a simple random sample has been selected from a population with a normal distribution. Nicotine in menthol cigarettes 90% confidence; n= 23, S=0.26 mg. A Click the icon to view the table of Chi-Square critical values. df = Type a whole number.) Area to the right of the critical value Chi-Square (X²) Distribution Area to the Right of the Critical Value Degrees of Freedom Degrees of Freedom 0.995 0.99 0.975 0.95 0.90 0.10 0.05 0.025 0.01 0.005 1. 0.001 0.004 0.016 2.706 3.841 5.024 6.635 7.879 2 0.020 0.051 0.103 0.211 4.605 5.991 7.378 9.210 10.597 0.010 3. 0.072 0.115 0216 0.352 0.584 6251 7.815 9.348 11.345 12.838 4. 0.207 0.297 0.484 0.711 1.064 7.779 9.488 11.143 13.277 14.860 4. 0.412 0.554 0.831 1.145 1.610 9.236 11.071 12833 15.086 16.750 0.676 0.872 1.237 1.635 2.204 10.645 12.592 14.449 16.812 18.548 6. 0.989 1.239 1.690 2.167 2833 12.017 14.067 16.013 18.475 20.278 7. 1344 1.646 2.180 2.733 3.490 13.362 15.507 17.535 20.090 21.955 9 1.735 2.088 2.700 3.325 4.168 14.684 16.919 19.023 21.666 23.589 9. 10 2156 2.558 3.247 3.940 4.865 15.987 18.307 20.483 23.209 25.188 10 Help me solve this View an 11 2.603 3.053 3.816 4.575 5.578 17.275 19.675 21.920 24.725 26.757 11

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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The text provides instructions for determining the number of degrees of freedom, critical values (\( \chi_1^2 \) and \( \chi_2^2 \)), and the confidence interval estimate of \( \sigma \) for a sample. It's assumed that a simple random sample has been selected from a normal distribution. Specifically, the example involves nicotine in menthol cigarettes with a 90% confidence interval, \( n = 23 \), and \( s = 0.26 \) mg.

The text also describes accessing a table of Chi-Square critical values and includes a depiction of such a table for different degrees of freedom and the area to the right of the critical value (\( \chi^2 \) distribution).

### Chi-Square (\( \chi^2 \)) Distribution Table:
- **Degrees of Freedom** (df) are listed vertically on the left.
- **Areas to the Right of the Critical Value** columns represent significance levels from 0.995 to 0.005.
- For example:
  - For 1 degree of freedom, the critical value for 0.995 area is 0.000.
  - Similarly, for 10 degrees of freedom and an area of 0.05, the critical value is 18.307.

### Additional Interface Elements:
- **df input**: There is a prompt to type a whole number for degrees of freedom.
- **Help**: Options labeled "Help me solve this" and "View an example" suggest resources for further assistance.

Overall, the content aims to guide users in understanding and calculating intervals using Chi-Square distributions in statistical analysis.
Transcribed Image Text:The text provides instructions for determining the number of degrees of freedom, critical values (\( \chi_1^2 \) and \( \chi_2^2 \)), and the confidence interval estimate of \( \sigma \) for a sample. It's assumed that a simple random sample has been selected from a normal distribution. Specifically, the example involves nicotine in menthol cigarettes with a 90% confidence interval, \( n = 23 \), and \( s = 0.26 \) mg. The text also describes accessing a table of Chi-Square critical values and includes a depiction of such a table for different degrees of freedom and the area to the right of the critical value (\( \chi^2 \) distribution). ### Chi-Square (\( \chi^2 \)) Distribution Table: - **Degrees of Freedom** (df) are listed vertically on the left. - **Areas to the Right of the Critical Value** columns represent significance levels from 0.995 to 0.005. - For example: - For 1 degree of freedom, the critical value for 0.995 area is 0.000. - Similarly, for 10 degrees of freedom and an area of 0.05, the critical value is 18.307. ### Additional Interface Elements: - **df input**: There is a prompt to type a whole number for degrees of freedom. - **Help**: Options labeled "Help me solve this" and "View an example" suggest resources for further assistance. Overall, the content aims to guide users in understanding and calculating intervals using Chi-Square distributions in statistical analysis.
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