Answer:
A. Plant 1 is growing at a faster rate than Plant 2.
Step-by-step explanation:
The slope (m) or rate of growth in Plant 1 is;
m = Change in y ÷ change in x
m = 
= 2
The linear equation of growth in Plant 1 is;
= 2
y = 2x + 1.5
The equation of growth in Plant 2 is; y = 1.5x + 3 (slope of 1.5)
Since the slope in growth of Plant 1 is greater than that in Plant 2, it implies then that Plant 1 is growing at a faster rate than Plant 2.
Answer:
-22,-6,-5,0,3,7,10
Step-by-step explanation:
It would be the highest negative integers in front, so going down, you'd reach 0. Then go up positive number 3,7,10.
Answer:
x=10, y=25
Step-by-step explanation:
First, in a trapezoid, the two angles on the same leg (the legs are the opposite sides that are not parallel) add up to 180 degrees. Therefore, 4y as well as (2y+3x) are supplementary. We can write this out as
4y + (2y+3x) = 180
6y+3x = 180
Next, the angles of a triangle add up to 180 degrees. Therefore, as the angles 2y, 4y, and (5x-20) make up a triangle, they add up to 180 degrees. We can write this as
4y + 2y + (5x-20) = 180
6y + 5x -20 =180
Our two equations are thus
6y + 5x - 20 = 180
6y + 3x = 180
If we subtract 6y from both sides in each equation, we can say
5x - 20 = 180-6y
3x = 180-6y
Therefore, we can write
5x-20 = 180-5y = 3x
5x-20=3x
subtract 3x from both sides to make all x variables on the same side
2x-20 = 0
add 20 to both sides to isolate the x and its coefficient
2x = 20
divide both sides by 2 to isolate x
x = 10
Therefore,
x = 10
6y + 3x = 180
6y + 30 = 180
subtract 30 from both sides to isolate the y and its coefficient
6y = 150
y = 25
<u>Answer:</u>
<u>Null hypothesis: Policy B remains more effective than policy A.</u>
<u>Alternate hypothesis: Policy A is more effective than policy B.</u>
<u>Step-by-step explanation:</u>
Remember, a hypothesis is a usually tentative (temporary until tested) assumption about two variables– independent and the dependent variable.
We have two types of hypothesis errors:
1. A type I error occurs when the null hypothesis (H0) is wrongly rejected.
That is, rejecting the assumption that policy B remains more effective than policy A when it is <em>actually true.</em>
2. A type II error occurs when the null hypothesis H0, is not rejected when it is actually false. That is, accepting the assumption that policy B remains more effective than policy A when it is <em>actually false.</em>
