Answer:
lleva 10 000 tornillos un contenedor
Step-by-step explanation:
Answer:
3600 gallons of water was removed from the basement.
Step-by-step explanation:
Given:
Rate of each pump = 40 gallons/min
We need to find find the number of gallons of water removed from the basement.
Solution:
Now Given:
After half an hour, the one pump burns out.
Now we know that;
1 hour = 60 mins
hour = 
Now for 30 mins both the pumps were working and removing the water.
So we can say that;
Water remove for first 30 mins = 
Also Given:
the second pump finishes removing the water half an hour later.
So we can say that;
Water removed for next 30 mins = 
Now we can say that;
Total water removed from the basement is equal to sum of Water remove for first 30 mins and Water removed for next 30 mins .
framing in equation form we get;
Total water removed from the basement = 
Hence 3600 gallons of water was removed from the basement.
I uploaded it here as the answers Bc
Slkwowkneojw
Answer:
- 6 2/3 qt 80%
- 13 1/3 qt 20%
Step-by-step explanation:
It is often convenient to solve a mixture problem by letting a variable represent the quantity of the higher-concentration contributor to the mix.
__
We can let x represent the number of quarts of 80% solution needed. Then (20-x) is the number of quarts of 20% solution needed. The amount of salt in the final mix is ...
0.80x +0.20(20-x) = 0.40(20)
0.60x = 0.20(20) . . . . . . . . subtract 0.20(20) and simplify
x = 20/3 = 6 2/3 . . . . . . . . . divide by 0.60; quarts of 80% solution
(20 -x) = 13 1/3 . . . . . . . . . . amount of 20% solution needed
The teacher should mix 6 2/3 quarts of 80% solution with 13 1/3 quarts of 20% solution.
Complete question is;
Regarding the violation of multicollinearity, which of the following description is wrong?
a. It changes the intercept of the regression line.
b. It changes the sign of the slope.
c. It changes the slope of the regression line.
d. It changes the value of F-tests.
e. It changes the value of T-tests
Answer:
a. It changes the intercept of the regression line
Step-by-step explanation:
Multicollinearity is a term used in multiple regression analysis to show a high correlation between independent variables of a study.
Since it deals with independent variables correlation, it means it must be found before getting the regression equation.
Now, looking at the options, the one that doesn't relate with multicollinearity is option A because the intercept of the regression line is the value of y that is predicted when x is 0. Meanwhile, multicollinearity from definition above does in no way change the intercept of the regression line because it doesn't predict the y-value when x is zero.