\begin{tabular}{l} In a re-analysis of published studies, Twenge and Im (2007) found that for the \\ time period 1958-2001, the need for social approval of people in the United \\ States was negatively correlated with the U.S. divorce rate during the same \\ period (the correlation coefficient was -0.38). This correlation means that _- \\ divorce rates were high when the need for social approval was high \\ the need for social approval spurred people to divorce \\ the need for social approval prevented people from seeking divorce \\ divorce rates were low when the need for social approval was high \\ \hline\end{tabular}

Many investors and financial analysts believe the Dow Jones Industrial Average (DJIA) gives a good barometer of the overall stock market. On January 31, 2006, 9 of the 30 stocks making up the DJIA increased in price (The Wall Street Journal, February 1, 2006). On the basis of this fact, a financial analyst claims we can assume that \( 30 \% \) of the stocks traded on the New York Stock Exchange (NYSE) went up the same day. A sample of 76 stocks traded on the NYSE that day showed that 10 went up. You are conducting a study to see if the proportion of stocks that went up is is significantly less than 0.3 . You use a significance level of \( \alpha=0.002 \). What is the test statistic for this sample? Use \( \hat{p} \) rounded to 4 decimal places. (Report answer accurate to 4 decimal places.) test statistic \( =-3.198^{\circ} \times \)

Question 2 ( 0.25 points) Retake question Choose the correct interpretation of a p-value. If the test is right-tailed, the \( p \)-value is the probability of observing a sample proportion as small as we saw in our sample, if the null hypothesis were true. If the test is right-tailed, the \( p \)-value is the probability of observing a sample proportion as large as we saw in our sample, if the null hypothesis were true. If the test is right-tailed, the \( p \)-value is the probability of observing a sample proportion as large as we saw in our sample. If the test is two-tailed, the \( p \)-value is the probability of observing a sample proportion as far away from the null value as what was observed in the current data set.

Use this set of numbers to answer the question. \( \begin{array}{l}4,11,6,9,23,34,6,19 \\ \text { What is the median for this set of numbers? } \\ \text { A. } 6 \\ \text { B. } 10 \\ \text { D. } 14 \\ \text { D. } 16\end{array} \)

\( n = 5 \quad p ( \overline { x } > 500 ) \)

Find the mean of: \( 1.8,1.7,1.3,1.1,1.2,1.6,1.8 \) A. 1.6 B. 1.4 C. 1.8 D. 1.1 E. 1.5