Answer:
6x^2 +14x
Step-by-step explanation:
Multiply using the distributive property.
Answer:
<h2>Infinitely many solutions</h2>
Step-by-step explanation:


Answer:
The expression that represents his total time is given by "t = 7.5/s" where s is his speed against the wind.
Step-by-step explanation:
In order to solve this problem we will assign a variable to Curtis speed on the first leg of the trip, this will be called "s". Since the speed on the first part is "s" and the speed on the second part is 20% higher, then the speed on the second part is "1.2s". Each leg of the course is 9 miles long, therefore the time it took to go each way is given by:
time = distance/speed
First part:
t1 = 9/s
Second part:
t2 = 9/1.2s = 7.5/s
The expression for the whole course is the sum of each, so we have:
t = t1 + t2
t = 9/s + 7.5/s
t = (9 + 7.5)/s = (16.5)/s
X=pounds of coffee bean ($0.20 per pound)
y=pounds of coffee bean ($0.68 per pound )
We can suggest this system of equations:
x+y=120
(0.20x+0.68 y) / (x+y)=0.54 ⇒ (0.2x+0.68y)=0.54(x+y)
We can solve this system by substitution method.
x+y=120 ⇒ y=120-x
0.2x+0.68(120-x)=0.54[x+(120-x)]
0.2x+81.6-0.68x=0.54(120)
-0.48x+81.6=64.8
-0.48x=64.8-81.6
-0.48x=-16.8
x=-16.8/-0.48
x=35
y=120-x=120-35=85
Answer: the coffee mixture has 35 pounds of coffee beans sold to $0.2 a pound, and 85 pounds of coffee beans sold to $0.68 a pound, the solutions is reasonable because the price of a coffee mixture ($0.54 a pound) is greater than $0.2 and smaller than $0.68.
Answer:
A. The first equation is for sample data; the second equation is for a population.
Step-by-step explanation:
The first equation is y =
, this is the equation for sample data as the intercept (
) and the slope parameter(
) both are calculated then we have got this and these values are not taken as given.
The Second equation is
, this is the equation for population data as we can't calculate these
and
as we take these values as given and also we do testing for
parameter using t test and it is sure that testing is always done on population data not on sample data.