Answer:
C. 128ft
Step-by-step explanation:
it's C because whenever it says and you're supposed to multiply always remember that :) = (which means area ofc) you're finding the so you multiply 16x8 and the you get your answer (: ignore the 640 you just focus on the 16 and 8 ok? 16x8=128! :))
<em /><em> </em><em /><em /><em /><em /><em /><em /><em /><em> </em><em /><em /><em /><em /><em> </em><em /><em /><em> </em><em /><em /><em /><em /><em /><em /><em> </em><em /><em /><em /><em /><em /><em> </em><em /><em /><em> </em><em /><em /><em> </em><em /><em /><em /><em> </em><em /><em /><em /><em> </em><em /><em /><em> </em><em /><em /><em /><em /><em /><em> </em><em /><em /><em /><em /><em> </em><em /><em /><em /><em /><em /><em /><em /><em> </em><em /><em /><em> </em><em /><em /><em /><em /><em /><em> </em><em /><em /><em /><em /><em /><em /><em /><em /><em /><em> </em><em> </em><em>></em><em>:</em><em>(</em>
Answer:
27 is correct.
Step-by-step explanation:
Question 1: (0,2) because b value in mx+b is y-intercept
Question 2: plug in 4 for x you will get 1 so max is (4, 1)
Question 3: plug in -4 for x you will get -5 so min is (-4, -5)
Hope it helps :D
Answer:
Step-by-step explanation:
<em>Key Differences Between Covariance and Correlation
</em>
<em>The following points are noteworthy so far as the difference between covariance and correlation is concerned:
</em>
<em>
</em>
<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.
</em>
<em>2. Covariance is nothing but a measure of correlation. On the contrary, correlation refers to the scaled form of covariance.
</em>
<em>3. The value of correlation takes place between -1 and +1. Conversely, the value of covariance lies between -∞ and +∞.
</em>
<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.
</em>
<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.
</em>
You can find more here: http://keydifferences.com/difference-between-covariance-and-correlation.html#ixzz4qg5YbiGj
