While conducting a t-test, alpha is set at 0.5. Therefore we can conclude that:

OPTIONS

• 95% of the time, our decision will be correct.
• 5% of the time, we will claim that there is a real difference when there really is not a difference.
• the data will be 95% accurate.
• 5% of the time, we will say that there is no real difference, but in reality, there is a difference.

ANSWER

5% of the time, we will claim that there is a real difference when there really is not a difference.

EXPLANATION

An alpha risk or Type-I risk is risk of rejecting a true hypothesis. A t-test evaluates the equality of two sample means: If alpha = 0.05, the null hypothesis will be rejected (says there is a difference) when the null hypothesis should not be rejected (no evidence of a difference) 5% of the time.