Luke and Joshua work at a dry cleaners ironing shirts. Luke can iron 35 shirts per hour, and Joshua can iron 25 shirts per hour. Luke worked 3 more hours than Joshua and they ironed 345 shirts between them. Determine the number of hours Luke worked and the number of hours Joshua worked.
Answers
Answer:
48
Step-by-step explanation:
I solved the problem step by step on paper and got it right
Related Questions
Find the value for X and Y
What is the volume of a hemisphere with a radius of 9.7 cm, rounded to the nearest tenth of a cubic centimeter? please i need help ill do a zoom call and i'll give you all my Branly points if uu help me.
For a cone, if the radius was quadrupled and the slant height was reduced to 1/6 of its original size what would be the formula to find the modified surface area.
Need help on this pls
0.9, 75%, 4/5
Answers
smallest to largest:
4/5, 0.9, 75%
hope I helped... :D
Answers
Answer:
2n(n + 5)(n + 6)
Step-by-step explanation:
given the expression
2n³ + 22n² + 60n ← factor out the common factor of 2n from each term
= 2n(n² + 11n + 30) ← factorise the quadratic
consider the factors of the constant term (+ 30) which sum to give the coefficient of the n- term (+ 11)
the factors are + 5 and + 6 , since
+ 5 × + 6 = + 30 and 5 + 6 = + 11
use these factors to split the n- term
n² + 5n + 6n + 30 ( factor the first/second and third/fourth terms )
= n(n + 5) + 6(n + 5) ← factor out (n + 5) from each term
= (n + 5)(n + 6)
Then
2n³ + 22n² + 60n
= 2n(n + 5)(n + 6) ← in factored form
Answers
Answer:
y = -5
Step-by-step explanation:
- 4y - 3 + 2y = 7y + 2
- 4y - 7y + 2y = 3 + 2
- -y = 5
- y = -5
Brainliest me please :(
Answer:
Y=-5
Step-by-step explanation:
-4y on each side then -2y on each side so it is know -3=y+2. Y must be -5 because -3-2=-5
Answers
Answer:they are both linear because Their slopes are constant.
Step-by-step explanation:
January February March April May June
Acutal 120 140 150 140 150 130
Predicted 80 150 110 150 110 150
Residual 40 −10 40 −10 40 −20
Analyze the data. Determine whether the equation that produced the predicted values represents a good line of best fit.
No, the equation is not a good fit because the residuals are all far from zero.
No, the equation is not a good fit because the sum of the residuals is a large number.
Yes, the equation is a good fit because the residuals are not all far from zero.
Yes, the equation is a good fit because the sum of the residuals is a small number.
Answers
The equation that produced these predicted values is not a good fit given that the sum of the residuals is a large number.
What is the sum of the residuals in a regression equation?
The sum of the residuals in a regression is a value that is always supposed to be almost equal to zero in a regression analysis.
The residual tells us that the error term has been reduced to the minimum in the regression analysis.
Read more on a regression analysis here:
#SPJ5
Answers
Xsquere=49
X=√49 (squere root of 49 is 7)
i.e X=7