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 \( =-3.198^{\circ} \times \)

A national food brand wants to launch a new chip flavor. They run a test study and offer 3 new flavors in select stores around the country.What's the best measure for determining which flavor to launch?Total revenue before and after offering the new flavorsSocial media surveysSales data and frequency of repeat purchases for the new flavorsDiscussions with customers in the stores offering the new flavorsTotal sales for stores offering the new chips against those that are not

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

Select all of the possible null hypotheses from the list below. \( p=0.37 \) \( p>0.84 \) \( p<0.42 \) \( p \neq 0.10 \)

\( 11,16,12,7,23,9,5,5 \) What is the median of the data? B. 10 D. 11 D. 18

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.