Final answer:
When the significance level is decreased to reduce the chance of a Type I error, the chance of a Type II error increases.
Step-by-step explanation:
When the colleague suggests running the statistical test with an alpha of .01 instead of .05, it means that the significance level is decreased. A lower alpha value means that we are setting a stricter criteria for rejecting the null hypothesis. This reduces the chance of a Type I error (rejecting the null hypothesis when it is true), as we are less likely to falsely conclude that there is a significant difference.
However, reducing the chance of a Type I error by decreasing the alpha level also increases the chance of a Type II error (failing to reject the null hypothesis when it is false). This means that the test becomes less sensitive at detecting a true difference, as we are more likely to miss a significant result.
Therefore, the correct answer is option 1) It will increase.