He had 40 pencils left after he gave away 8, so originally he had 40 + 8 pencils, which is 48.
Now, he bought 4 packages, which had a total of 48 pencils, so divide 48 by 4, which is 12. He had 12 pencils in each package.
To determine the solution arithmetically, first add 8 to 40, then divide 48 by 4.
To determine the solution algebraically, set up and solve the equation 40 = 4x - 8.
Each package contained 12 pencils.
Hope this helps
Answer:
There were 172 guests that were children and 278 guests that were adults
Step-by-step explanation:
Step 1: State what is known
It is $25 per adult
It is $12 per child
The made $9014 dollars
There were 450 guests
Step 2: Define equations
25y + 12x = 9014 -----1
x + y = 450 ------------2
Step 3: Rearrange equation 2 for x
x + y = 450
x = 450 - y --------------3
Step 4: Substitute 3 into 1 for y and solve for y
25y + 12(450 - y) = 9014
25y + 5400 - 12y = 9014
13y = 3614
y = 3614/13
y = 278
Step 5: Substitute y = 278 into 3 to solve for x
x = 450 - (278)
x = 172
Therefore 172 children and 278 adults visited the museum
Answer:
D. The difference of the means is not significant because the re-randomizations show that it is within the range of what could happen by chance.
Step-by-step explanation:
The treatment group using System A reported a mean of 18.5 lost bags per day. The treatment group using System B reported a mean of 16.6 lost bags per day.
The best conclusion that can be made is - The difference of the means is not significant because the re-randomizations show that it is within the range of what could happen by chance.
As we know, in statistics, nothing happens by chance. So, this option is correct.
Answer:
<h2><em>
y = 10</em></h2>
Step-by-step explanation:
11y - 6 = 104
11y = 104 + 6
11y = 110
y = 110 :11
y = 10
_____________
check
11*10-6=104
110=104+6
110=110
the answer is good
Answer:
(a) there is a little difference in proportion clearly from the data given as observed.
(B) if a conclusion In the test part (a) is incorrect then a type 1 error was made.
Step-by-step explanation:
In statistical hypothesis testing:
type I error is the rejection of a true null hypothesis while
a type II error is the non-rejection of a false null hypothesis.
