The denominator( s ) we are given are 
, and . The first thing we want to do is factor the expressions, to make this easier -
This expression is a perfect square, as ( x )^2 = x^2, ( 2 )^2 = 4, 2 * ( x ) * ( 2 ) = 4x. Thus, the simplified expression should be the following -
The other expression is, on the other hand, not a perfect square so we must break this expression into groups and attempt factorization -
Combining ( x + 2 )^2 and ( x + 2 )( x + 3 ), the expression that contains factors of each is ( x + 2 )^2 * ( x + 3 ), or in other words the LCM.
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66.5 divided by 3.5 is 19.
Answer:
You are correct
Step-by-step explanation:Nice job have a nice day!!!
When calculating correlation and regression both sets of data must be Statistical.
According to the statement
we have to find the type of data when we calculate the correlation and regression both sets.
so, The difference between these two statistical measurements is that correlation measures the degree of a relationship between two variables (x and y), whereas regression is how one variable affects another.
And when we calculate both then data sets must be a statistical data. because correlation summarizing direct relationship between two variables and regression predict or explain numeric response. So, without statistical data this is not possible to calculate correlation and regression both sets.
so, When calculating correlation and regression both sets of data must be Statistical.
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8t+32 is one expression equivalent to that.
