Researchers selected 894 patients at random among those who take a certain widely-used prescription drug daily. In a clinical trial, 28 out of the 894 patients complained of flulike symptoms. Suppose that it is known that \( 2.9 \% \) of patients taking competing drugs complain of flulike symptoms. Is there sufficient evidence to conclude that more than \( 2.9 \% \) of this drug's users experience flulike symptoms as a side effect at the \( \alpha=0.1 \) level of significance? Find the P-value. P-value \( =\square \) (Round to three decimal places as needed.)

By selecting a smaller alpha level, a researcher is: attempting to make it easier to reject the null (HO). attempting to make it easier to reject the alternative (H1). reducing the risk of a Type I error. attempting to decrease the standard error.

A researcher rejects the null hypothesis only if the obtained statistical results show: that it is likely that the null is true. that it is unlikely that the null is true. that it is likely that the alternative hypothesis is false. that is unlikely that the alternative hypothesis is false.

If we say that we have statistically significant results, we mean that the results are: very important. meaningless. likely to be due to chance differences between to be due to true differences between the groups.

A researcher risks a Type I error: anytime HO is rejected. anytime H 1 is rejected. anytime HO is accepted. anytime the sample size is increased.

The null hypothesis: predicts that the treatment will have no effect. predicts that the treatment will have an effect. is denoted by the symbol H1. is always stated in terms of sample statistics.