Answer: 12.07 ounce/gallon.
Step-by-step explanation:
given data:
desired ratio = 90grams / liter of water.
ratio In ounce/ gallon
first we convert our grams to ounce
= 98grams / 28.35
= 3.175 ounce.
converting liter to gallons
= 1/3.8
=0.263 gallons
therefore;
= 3.175 ounce / 0.263 gallons
= 12.07 ounce/gallon.
Answer:

Step-by-step explanation:
Fraction of the total that is for corn (TC - Total corn):

fraction of the corn section that is for white corn (WC - white corn in the corn seccion):

we need to find the fraction of the whole field that is for the white corn.
For this we need to find how much is
out of the
destinated to corn, and this will be the fraction of the total that is for white corn. We find this fraction by multiplying the fraction of corn (
) by the fraction of white corn in the corn section (
).
I will call the total fraction of white corn TWC, thus:

the answer is:
of the whole field is planted with white corn
Answer:
Correct option: third one -> 11.5 m3
Step-by-step explanation:
To find the volume of the ramp, first we need to find the volume of the rectangular prism and the volume of the triangular prism:
V_rectangular = 4m * 2m * 1m = 8 m3
V_triangular = (2m * 3.5m * 1m) / 2 = 3.5 m3
Now, to find the volume of the ramp, we just need to sum both volumes:
V_total = V_rectangular + V_triangular = 8 + 3.5 = 11.5 m3
Correct option: third one.
Answer:
Residual = -2
The negative residual value indicates that the data point lies below the regression line.
Step-by-step explanation:
We are given a linear regression model that relates daily high temperature, in degrees Fahrenheit and number of lemonade cups sold.

Where y is the number of cups sold and x is the daily temperature in Fahrenheit.
Residual value:
A residual value basically shows the position of a data point with respect to the regression line.
A residual value of 0 is desired which means that the regression line best fits the data.
The Residual value is calculated by
Residual = Observed value - Predicted value
The predicted value of number of lemonade cups is obtained as

So the predicted value of number of lemonade cups is 23 and the observed value is 21 so the residual value is
Residual = Observed value - Predicted value
Residual = 21 - 23
Residual = -2
The negative residual value indicates that the data point lies below the regression line.
For this case, the first thing you should know is that the speed of the transfer is given by
Speed = Megabytes / time
Substituting
V = (549) / (125)
V = 4.392 mb / s
answer
the speed of the transfer was 4,392 mb / s