Part ii: true/false correct any false statements. 2. a confidence interval widens as its confidence level increases. 3. a confidence interval widens as its sample size increases. 4. confidence levels refer to the probability that the interval will capture the true parameter in repeated samples. they are not the likelihood that particular intervals contain the true parameter. 5. one-sided hypothesis tests are used when we are stating that a parameter is larger than the null hypothesis value. 6. when the p-value > , there is enough evidence to reject the null hypothesis. 7. not having enough evidence to reject the null hypothesis and concluding that the null hypothesis is true are equivalent statements.