If we set alpha at 0.05 instead of 0.01, other factors held constant . greater risk of a Type I error and a lower risk of a Type II error greater risk of a Type I error and a greater risk of a Type II error a lower risk of a Type I error and a greater risk of a Type II error a lower risk of a Type I error and a lower risk of a Type II error

greater risk of a Type I error and a lower risk of a Type II error

Step-by-step explanation:

Remember, in statistics, alpha (or the significance level) α,  refers to the probability of rejecting the null hypothesis when it is true.

Hence, setting alpha at 0.05 (or 5%) instead of 0.01 (or 1%) implies that the researcher is increasing how far away the statistics data needs to be from the null hypothesis value before they can decide to reject the null hypothesis. In other words, a probability of 5% is greater than 1%, resulting in a greater risk of a Type I error and a lower risk of a Type II error.

easy its decreasing

step-by-step explanation:

because its top point is at the to of the graph on the left side (atleast from the veiw i see it) now if that top point wast in the lower part of the graph it would be increasing hope this have a nice day

might be the correct answer will be question number 2