Answer:
b, since the others have the input and output on the wrong sides
Answer: 4
Step-by-step explanation:
(g*h)(5) = 4
Firstly, h(5) = 5 - 7 = -2
Then, evaluate g(-2) = (-2)^2 = 4
Answer:
X= 5, -9
Step-by-step explanation:
(X+2)² =49
Expand the bracket,
(X+2) (X+2)= 49
Apply the distributive property;
X(X+2) +2 (X+2) =49
X²+2X+2X+4=49
X²+4X+4=49
Move 49 to the left side of the equation;
X²+4X+4-49=0
X²+4X-45=0
Apply Factorisation method;
Consider the form
a²+bx+c=0
Find two numbers whose sum is equal to b and whose product is equal to c.
Comparing with our equation;
B =4 and C =45
We can use 9 and -5, this is because ;
9+(-5)=4 and 9*(-5)= 45.
Replace X +4X-45=0 with (X-5) (X+9)=0
Therefore;
X-5=0
X+9=0
Moving to the left side of the equation;
Therefore X= 5 and -9
She saved up a total of $82.60, and had to spend a total of $60.90, so she would have $21.70 left and need to save up another $180.40, hope this helps
Complete question :
According to the National Beer Wholesalers Association, U.S. consumers 21 years and older consumed 26.9 gallons of beer and cider per person during 2017. A distributor in Milwaukee believes that beer and cider consumption are higher in that city. A sample of consumers 21 years and older in Milwaukee will be taken, and the sample mean 2017 beer and cider consumption will be used to test the following null and alternative hypotheses:
H, :μ< 26.9
Ha : μ> 26.9
a. Assume the sample data led to rejection of the null hypothesis. What would be your conclusion about consumption of beer and cider in Milwaukee?
b. What is the Type I error in this situation? What are the consequences of making this error?
c. What is the Type II error in this situation? What are the consequences of making this error?
Answer:
Kindly check explanation
Step-by-step explanation:
Given the null and alternative hypothesis :
H0 :μ< 26.9
Ha : μ> 26.9
Assume the Null hypothesis is rejected ;
We conclude that there is significant evidence that the mean consumption of beer and cider is higher in the city (more than 26.9 gallons).
B.) Type 1 error is committed when the Null hypothesis is incorrectly rejected.
C.) Type 2 error is committed when we fail to reject a false null hypothesis. In this scenario, we fail to conclude that the average consumption of beer and cider is more than 26.9 gallons per person.
