In the context of hypothesis testing, which of the following is a reason that data may be considered unreliable?

• A. The null hypothesis is stated in terms of population parameters.
• B. The significance level is set to $0.05$.
• C. The data were collected using a biased sampling method.
• D. The test statistic is calculated using the sample mean.

Answer: (C)

Verified step by step guidance

1. Understand that in hypothesis testing, the reliability of data depends largely on how the data were collected and whether the sample represents the population well.
2. Recognize that stating the null hypothesis in terms of population parameters is standard practice and does not affect data reliability; it simply defines what is being tested.
3. Note that setting the significance level (e.g., 0.05) is a conventional choice to control the probability of Type I error and does not inherently make data unreliable.
4. Understand that calculating the test statistic using the sample mean is a normal procedure in many tests and does not compromise data reliability.
5. Identify that data collected using a biased sampling method can lead to unreliable results because the sample may not accurately represent the population, introducing systematic errors.