Identify factors that influence the significance level and power of a hypothesis test. Which of the following statements is FALSE? a. Alpha (a) is equal to the probability of making a Type I error.
b. A smaller sample size would increase the effectiveness of a hypothesis test.
c. The probability of rejecting the null hypothesis when the null hypothesis is true is called a Type 1 Error.
d. The power of a hypothesis test is the probability of not making a Type Il error.

b. A smaller sample size would increase the effectiveness of a hypothesis test.

Step-by-step explanation:

A hypothesis test is an important procedure in the field of statistics. It evaluates any two mutually exclusive statements about a population that determines and tells which statement made best supports to the sample data provided.

Now we know that an increase in the sample size makes the hypothesis test more effective and sensitive and it is more likely to reject the null hypothesis.

The probability of making a type I error is known as the Alpha while the probability of making type II error is called Beta.

Thus the correct option is (b).

sas (side angle side)

aa(angle angle)

sss(side side side)

sas you have to find two sides with an angle in between

aa you find two angles because it will always add up to 180

sss find all sides

step-by-step explanation:

answer: bea's uncle is 25 years old.

step-by-step explanation:

given the equation , we can say that the variable "x" represents the age of bea's uncle. then to find his age, we need to solve for "x":

we must add 15 to both sides of the equation:

now we need to divide both sides of the equation by 3:

therefore, we can conclude that bea's uncle is 25 years old.