Answer:
20%
Step-by-step explanation:
(60 - 48) / 60 = 0.2 (20%)
Hello!
√7 - y = 6 <=>
<=> -y = 6 - √7 <=>
<=> y = -6 + √7 => √7 - (-6 + √7) = 6
Good luck! :)
Answer:
Domain of the function is (inf, -inf)
Step-by-step explanation:
Answer:
And we can find this probability using the complement rule and with the normal standard table or excel:
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".
Solution to the problem
Let X the random variable that represent the average household spent of a population, and for this case we know the distribution for X is given by:
Where
and
We are interested on this probability
And the best way to solve this problem is using the normal standard distribution and the z score given by:
If we apply this formula to our probability we got this:
And we can find this probability using the complement rule and with the normal standard table or excel:
The (i,j) minor of a matrix A is the matrix Aij obtained by deleting row i and column j from A it is true.
The (i,j) minor of a matrix A is the matrix Aij obtained by deleting row i and column j from A. A determinant of an n×n matrix can be defined as a sum of multiples of determinants of (n−1)×(n−1) sub matrices.
This is done by deleting the row and column which the elements belong and then finding the determinant by considering the remaining elements. Then find the co factor of the elements. It is done by multiplying the minor of the element with -1i+j. If Mij is the minor, then co factor,
+
.
Each element in a square matrix has its own minor. The minor is the value of the determinant of the matrix that results from crossing out the row and column of the element .
Learn more about the minor of the matrix here:
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