Answer:
850
Step-by-step explanation:
Answer:
x= 7
Step-by-step explanation:
1st step: Multiply the factor (outside number) with the numbers and variable(s) in the box. This results in 2(x-3) = 2x-6
2nd Step: continue the rest of the equation since there are no more brackets left so 2x-6-12=-4
3rd Step: send -12 to the other side of the equation (side changes sign changes) so it will become 2x-6=-4+12 (You are actually supposed to make the variable alone on one side of the equation so that you would be able to calculate its value)
4th step: 2x-6=8 ---> send -6 to the other side as well which will then result in 2x=14
5th step: since 2 is being multiplied by x, when you send it to the other side (to make x alone) you will divide 14 by 2 ( sign of 2 changes from multiplication to division)
Final Step: x=7
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>
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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
