Answer:
A. 0.22
B. 0.18
C. 0.25
D. 0.244
Step-by-step explanation:
S = {51 to 100} = 50
The sample space S contains values from 51 to 100 which is a total of 50 different values.
A.
Probability of A (lies between the values of 90 to 100 = 11).
11/50 = 0.22
B.
For a student to fail the course, his course has to be less than 60 = from 51 to 59. A total of 9 values.
9/50 = 0.18
C.
For student to get c, (70 to 79) a total of 10 values: 10/50 = 0.20
P(student did not get C) = 1-0.20 = 0.80
To get B, ( 80 to 89)
10/50 = 0.20
Probability that a student who is known not to have a c grade has a b grade = 0.20/0.80 = 0.25
D.
Probability of passing lies between 60 to 100 = 41 scores
41/50 = 0.82
Probability of student who passed having a B = 0.20/0.82 = 0.244
Answer:
X density = fXpxq and
Y" =InpXq
Now to find Y density FYpyq interms of the density of X we compare the density of X with Y"
fX = In
And PXq =pxq
Thus replacing x with y,
PXq = pyq
(a) Hence the density of Y is FYpyq
(b) at p0, fYpyq =fYp0q= 0
At 5s, FYpyq =5
Answer:
scale factor = 5
Step-by-step explanation:
To determine the scale factor calculate the ratio of corresponding sides of the enlargement to the original, that is
scale factor = 
= 
= 5
Answer: Choice C
Amy is correct because a nonlinear association could increase along the whole data set, while being steeper in some parts than others. The scatterplot could be linear or nonlinear.
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Explanation:
Just because the data points trend upward (as you go from left to right), it does not mean the data is linearly associated.
Consider a parabola that goes uphill, or an exponential curve that does the same. Both are nonlinear. If we have points close to or on these nonlinear curves, then we consider the scatterplot to have nonlinear association.
Also, you could have points randomly scattered about that don't fit either of those two functions, or any elementary math function your teacher has discussed so far, and yet the points could trend upward. If the points are not close to the same straight line, then we don't have linear association.
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In short, if the points all fall on the same line or close to it, then we have linear association. Otherwise, we have nonlinear association of some kind.
Joseph's claim that an increasing trend is not enough evidence to conclude the scatterplot is linear or not.
First you distribute 4 to 2x and 3. Then after you do that you get 8x+12=10x
