Answer:
x =0,1,2,3,4,5,6
P(x) =0,4,8,12,16,20,24
Step-by-step explanation:
P(x)= 4x
4 x 1 = 4
4 x 2 = 8
4 x 3 =12
4 x 4 = 16
4 x 5 = 20
4 x 6 = 24
The given problem is very confusing since it was copy
pasted directly from the source so the equations look scrambled and plus it was
one words. After my own translation, I believe the given numbers are:
4 ⋅ 10^6
and
1 ⋅ 10^4
The symbol ⋅ means
that the two numbers are multiplied while the symbol ^ means an exponent of.
Now we are asked to find how much the 1st number is larger than the
2nd number. To solve this, we simply have to divide the bigger
number by the smaller number. Since 4 ⋅ 10^6
has bigger exponent than 1 ⋅ 10^4
then it is the bigger number.
Ratio = 4 ⋅ 10^6 /
1 ⋅ 10^4
Ratio = 4 ⋅ 10^2 =
400
Therefore 4 ⋅ 10^6
is 400 times bigger than 1 ⋅ 10^4.
Answer:
<span>400 times</span>
M=2/5 , (0,3)
use y= mx+c , find c first.
-3 = (2/5) 0 + c
c = -3
Thus the equation will be y=(2/5)x - 3.
or in some case,
(y1-y)=m(x1-x)
(-3-y)=(2/5)(0-x)
Answer:
C. Test for Goodness-of-fit.
Step-by-step explanation:
C. Test for Goodness-of-fit would be most appropriate for the given situation.
A. Test Of Homogeneity.
The value of q is large when the sample variances differ greatly and is zero when all variances are zero . Sample variances do not differ greatly in the given question.
B. Test for Independence.
The chi square is used to test the hypothesis about the independence of two variables each of which is classified into number of attributes. They are not classified into attributes.
C. Test for Goodness-of-fit.
The chi square test is applicable when the cell probabilities depend upon unknown parameters provided that the unknown parameters are replaced with their estimates and provided that one degree of freedom is deducted for each parameter estimated.
Answer:
the sampling distribution of proportions
Step-by-step explanation:
A sample is a small group of observations which is a subset of a larger population containing the entire set of observations. The proportion of success or measure of a certain statistic from the sample, (in the scenario above, the proportion of obese observations on our sample) gives us the sample proportion. Repeated measurement of the sample proportion of this sample whose size is large enough (usually greater Than 30) in other to obtain a range of different proportions for the sample is called the sampling distribution of proportion. Hence, creating a visual plot such as a dot plot of these repeated measurement of the proportion of obese observations gives the sampling distribution of proportions
