We can use elimination for these set of systems.
First, we need to set up our variables.
Belts=b
Hats=h
Now, the situation is 6 belts and 8 hats for $140. The situation after is 9 belts and 6 hats for $132.
Let’s set up our system of equations.
6b+8h=140
9b+6h=132
We need to eliminate a variable. Since b has coefficients of 6 and 9, we can easily eliminate b by multiplying the top equation by 3 and the bottom by -2.
18b+24h=420
-18b-12h=-264
Now let’s add.
12h=156
Let’s divide to get h by itself.
156/12=13=h
So a hat costs $13. We need to put in 13 for one of the equations so we can find the cost of a belt.
9b+6(13)=132
9b+78=132
We need b by itself.
9b=54
54/9=6
Belts are $6
We can also use the first equation to check our answers.
6(6)+8(13)
36+104
140.
So, the price of a belt is $6 while the price of a hat is $13.
Answer:
5/6
Step-by-step explanation:
5 is the amount of cheese pizzas Mrs. Jones ordered out of the 6 pizzas in total. 5 is a prime number, so the fraction cannot be simplified.
Answer:
46
Step-by-step explanation:
Answer:
B. There is not sufficient evidence at the 0.02 level of significance that the new technique reduces training time.
Step-by-step explanation:
We are given that using traditional methods it takes 107 hours to receive an advanced flying license.
A researcher believes the new technique may reduce training time and decides to perform a hypothesis test.
Let 
= <u><em>average training time to receive an advanced flying license</em></u>
So, Null hypothesis, 
: 
107 hours {means that the new technique doesn't reduce training time}
Alternate Hypothesis, 
: < 107 hours {means that the new technique may reduce training time}
Now, it is stated that after performing the test on 50 students, the researcher decides to reject the null hypothesis at a 0.10 level of significance.
As we know that if the test statistics value is rejected at a 10% level of significance, then it must not be rejected at the 0.02 level of significance.
This means that there is not sufficient evidence at the 0.02 level of significance that the new technique reduces training time because our null hypothesis has not been rejected.
I think it is 0.5 per min
