Answer:
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Step-by-step explanation:
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Answer:
OK, lets start by drawing a basic graph (the first one) so we can visualize.
We already know that the y coordinate of the circle's center is 
.
We know that the circle is tangent to the 
axis at 
That means the x coordinate of the center has to be 
, as the tangent is a point on the edge of the circle that touches a line at exactly one point.
The radius is the distance from the center of the circle to its edge. We know the center's location now, it is 
and a point on the edge of the circle (the tangent point) which is . so the distance between the points is 4 which is the radius (you can use the distance formula, but it's quite oblivious.)
We can imagine the circle should look like this (the second one):
Now we can piece together an equation
The equation of a circle is 
where 
is the center and 
is the radius. When we put the numbers in: we get 
which can be simplified into which is the answer.
Step-by-step explanation:
Ratio and proportion
convert to inproper fracton first
1 and 1/2=1+1/2=2/2+1/2=3/2
3 and 1/2=3+1/2=6/2+1/2=7/2
3/2dozen=7/2cups
times 2 both sides
3dozen=7cups
divide by 3 both sides
1dozen=7/3cups=2 and 1/3 cup
Answer:
Step-by-step explanation:
Correlation occurs when we can observe a trend between the response/dependent variable (y) and the explanatory/independent variable (x).
When comparing two sets of data, we may observe and use correlation to determine whether or not the data presented if significant or not and whether or not it supports our hypothesis. We may want to see if this is just a fluke and whether or not the trend causes causation.
An example of this would be if we thought that the weight of female mice determines how many kids they have in a month.. Let's say that mice that weigh up to one ounce have 6 baby mice per month.
Let's say that the x variable is the weight which is between 0.25 oz and 1.25 oz and the y-variable is the amount of kids between each month. If another laboratory conducts the same study with the same type of mice with the same weights as us, we would need to determine if there is correlation and if there is causation and try to use this information to determine if both sets of data are significant to our hypothesis.
Well, 1x5=5 and 2x5=10 so 3x5=15
