A sample of 20 items provides a sample standard deviation of 4. a. Compute the 90% confidence interval estimate of the population variance (to 2 decimals). Use Table 11.1. b. Compute the 95% confidence interval estimate of the population variance (to 2 decimals). Use Table 11.1. c. Compute the 95% confidence interval estimate of the population standard deviation (to 1 decimal). Use Table 11.1. sos
A sample of 20 items provides a sample standard deviation of 4. a. Compute the 90% confidence interval estimate of the population variance (to 2 decimals). Use Table 11.1. b. Compute the 95% confidence interval estimate of the population variance (to 2 decimals). Use Table 11.1. c. Compute the 95% confidence interval estimate of the population standard deviation (to 1 decimal). Use Table 11.1. sos
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A sample of 20 items provides a sample standard deviation of 4.

Transcribed Image Text:**TABLE 11.1: Selected Values from the Chi-Square Distribution Table**
This table provides selected values from the Chi-Square Distribution for various degrees of freedom and areas in the upper tail. The Chi-Square distribution is commonly used in statistical tests to assess the variance of a sample.
**Graph Explanation:**
- The graph at the top illustrates the Chi-Square distribution curve with the area in the upper tail highlighted. The horizontal axis is marked with \(\chi^2_\alpha\), representing the critical value for the specified area or probability.
**Table Details:**
- **Degrees of Freedom:** Listed in the first column, ranging from 1 to 100.
- **Area in Upper Tail:** This section corresponds to \( \alpha \) levels of 0.99, 0.975, 0.95, 0.90, 0.10, 0.05, 0.025, and 0.01.
Each cell in the table represents the Chi-Square value for a specific degrees of freedom and tail area.
**Sample Entries:**
- For 1 degree of freedom and an area of 0.05, the Chi-square value is 3.841.
- For 10 degrees of freedom and an area of 0.01, the Chi-square value is 19.675.
- For 40 degrees of freedom and an area of 0.05, the Chi-square value is 55.758.
*Note: A more extensive table is provided as Table 3 of Appendix B (available online). This provides additional Chi-Square values for further degrees of freedom and tail areas.*
This table is a valuable tool for statistical tests, allowing users to find critical values needed for hypothesis testing.
![A sample of 20 items provides a sample standard deviation of 4.
a. Compute the 90% confidence interval estimate of the population variance (to 2 decimals). Use Table 11.1.
[_____] ≤ σ² ≤ [_____]
b. Compute the 95% confidence interval estimate of the population variance (to 2 decimals). Use Table 11.1.
[_____] ≤ σ² ≤ [_____]
c. Compute the 95% confidence interval estimate of the population standard deviation (to 1 decimal). Use Table 11.1.
[_____] ≤ σ ≤ [_____]
(Note: There are no graphs or diagrams in the image.)](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F6b64a519-1474-49ec-8afb-98e9a37e1aea%2Fabb7477c-ac8d-4bc2-96fb-daf55990845b%2Fkxzsrbg_processed.png&w=3840&q=75)
Transcribed Image Text:A sample of 20 items provides a sample standard deviation of 4.
a. Compute the 90% confidence interval estimate of the population variance (to 2 decimals). Use Table 11.1.
[_____] ≤ σ² ≤ [_____]
b. Compute the 95% confidence interval estimate of the population variance (to 2 decimals). Use Table 11.1.
[_____] ≤ σ² ≤ [_____]
c. Compute the 95% confidence interval estimate of the population standard deviation (to 1 decimal). Use Table 11.1.
[_____] ≤ σ ≤ [_____]
(Note: There are no graphs or diagrams in the image.)
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