Answer:
87
Step-by-step explanation:
all the angles of a triangle out of 180 so subtract the two numbers you have from 180
We can use a system of equations in order to solve for both of the numbers. Let's start off by assigning variables to each number. The bigger number can be 'x', and the smaller number can be 'y'.
We can make two equations from the given:
x = 18 + y
("One number is 18 more than another number")
x + y = 36
("The sum of the numbers is 36")
If you look at the first equation, the variable 'x' already has a value (18 + y). We can input its value into the second equation in order to solve for y:
x + y = 36
(18 + y) + y = 36
18 + 2y = 36
2y = 18
y = 9
Input the value of 'y' into the first equation:
x = 18 + y
x = 18 + 9
x = 27
<u>One number is 27 and the other number number is 9.</u>
<u></u>
Let me know if you'd like me to explain anything I did here.
- breezyツ
Answer:
Step-by-step explanation:
<em>Key Differences Between Covariance and Correlation
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<em>The following points are noteworthy so far as the difference between covariance and correlation is concerned:
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<em>1. A measure used to indicate the extent to which two random variables change in tandem is known as covariance. A measure used to represent how strongly two random variables are related known as correlation.
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<em>2. Covariance is nothing but a measure of correlation. On the contrary, correlation refers to the scaled form of covariance.
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<em>3. The value of correlation takes place between -1 and +1. Conversely, the value of covariance lies between -∞ and +∞.
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<em>4. Covariance is affected by the change in scale, i.e. if all the value of one variable is multiplied by a constant and all the value of another variable are multiplied, by a similar or different constant, then the covariance is changed. As against this, correlation is not influenced by the change in scale.
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<em>5. Correlation is dimensionless, i.e. it is a unit-free measure of the relationship between variables. Unlike covariance, where the value is obtained by the product of the units of the two variables.
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You can find more here: http://keydifferences.com/difference-between-covariance-and-correlation.html#ixzz4qg5YbiGj