State your decision. Since the \( p \)-value is greater than .01 , reject \( H_{0} \). Since the \( p \)-value is greater than .01 , fail to reject \( H_{0} \). Since the \( p \)-value is less than .01, fail to reject \( H_{0} \). Since the \( p \)-value is less than .01 , reject \( H_{0} \).
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The correct decision based on the information provided is: Since the \( p \)-value is greater than .01, fail to reject \( H_{0} \). This means there is not enough evidence to conclude that the null hypothesis is false. In hypothesis testing, the \( p \)-value helps researchers understand the strength of the evidence against the null hypothesis. A \( p \)-value below the significance level (like .01) indicates strong evidence against \( H_{0} \), while a \( p \)-value above it indicates insufficient evidence, leading to a decision to fail to reject the null hypothesis.