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.

y < -3

step-by-step explanation:

-3y - 2 > 7

-3y -2 + 2 > 7+2

-3y > 9

-3y/-3 < 9/-3   (change the inequality sign when multiplying or dividing by a negative number)

y < -3