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$The accompanying data set lists full IQ scores for a random sample of subjects with medium lead levels in their blood and another random sample of subjects with high lead levels in their blood. Use a 0.01 significance level to test the claim that IQ scores of subjects with medium lead levels vary more than IQ scores of subjects with high lead levels. C. H_(0):sigma_(1)^(2)=sigma_(2)^(2) {:[H_(0):sigma_(1)^(2)=sigma_(2)^(2)],[H_(1):sigma_(1)^(2)!=sigma_(2)^(2)]:} H_(1):sigma_(1)^(2) > sigma_(2)^(2) Identify the test statistic. The test statistic is 2.82 . (Round to two decimal places as needed.) Identify the P-value. The P-value is ◻. (Round to three decimal places as needed.)$

The accompanying data set lists full IQ scores for a random sample of subjects with medium lead levels in their blood and another random sample of subjects with high lead levels in their blood. Use a $0$ . $01$ significance level to test the claim that IQ scores of subjects with medium lead levels vary more than IQ scores of subjects with high lead levels. $\newline$ C. $H_{0}: \sigma_{1}^{2}=\sigma_{2}^{2}$ $\newline$ $\begin{array}{l} H_{0}: \sigma_{1}^{2}=\sigma_{2}^{2} \\ H_{1}: \sigma_{1}^{2} \neq \sigma_{2}^{2} \end{array}$ $\newline$ \mathrm{H}_{1}: \sigma_{1}^{2}>\sigma_{2}^{2} $\newline$ Identify the test statistic. $\newline$ The test statistic is $2$ . $82$ . $\newline$ (Round to two decimal places as needed.) $\newline$ Identify the P-value. $\newline$ The P-value is $\square$ . $\newline$ (Round to three decimal places as needed.)

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Q. The accompanying data set lists full IQ scores for a random sample of subjects with medium lead levels in their blood and another random sample of subjects with high lead levels in their blood. Use a

0

01

significance level to test the claim that IQ scores of subjects with medium lead levels vary more than IQ scores of subjects with high lead levels.

\newline

H_{0}: \sigma_{1}^{2}=\sigma_{2}^{2}

\newline

\begin{array}{l} H_{0}: \sigma_{1}^{2}=\sigma_{2}^{2} \\ H_{1}: \sigma_{1}^{2} \neq \sigma_{2}^{2} \end{array}

\newline

\mathrm{H}_{1}: \sigma_{1}^{2}>\sigma_{2}^{2}

\newline

Identify the test statistic.

\newline

The test statistic is

2

82

\newline

(Round to two decimal places as needed.)

\newline

Identify the P-value.

\newline

The P-value is

\square

\newline

(Round to three decimal places as needed.)

State hypotheses: State the null and alternative hypotheses. $\newline$ $H_0: \sigma_1^2 = \sigma_2^2$ (The variances are equal) $\newline$ H_1: \sigma_1^2 > \sigma_2^2 (The variance of the first group is greater than the second group)
Identify statistic: Identify the test statistic. Given test statistic = $2.82$
Identify $P$ -value: Identify the $P$ -value. Given $P$ -value is missing, so we need to find it using the test statistic and the appropriate distribution table or software.
Find P-value: Find the P-value using the F-distribution table or software for the given test statistic. $\newline$ Since we don't have the actual data or distribution table, we cannot calculate the P-value here. Normally, you would look up the value of $2.82$ in the F-distribution table for the appropriate degrees of freedom or use statistical software to find the P-value.
Compare to significance level: Compare the P-value to the significance level. $\newline$ If $P$ -value < 0.01, we reject the null hypothesis. $\newline$ If $P$ -value > 0.01, we fail to reject the null hypothesis. $\newline$ Since we don't have the $P$ -value, we cannot complete this step.