x - 16 = 47 <em>add 16 to both sides</em>
x - 16 + 16 = 47 + 16
x = 63
Answer:
182
Step-by-step explanation:
2( \frac{1}{2} \times 4 \times 6 ) + 2( 5 \times 10 ) + ( 6 \times 10 )
= {182cm}^{2}
Answer:
moderate positive relationship
Step-by-step explanation:
From the data:
The linear relationship between score and rating can be obtained by calculating the Pearson correlation Coefficient between the two variables. This can be obtained more easily by using technology, a linear correlation Coefficient calculator. The result of the correlation Coefficient for the data above is about 0.66. This value is positive which shows that the association between the variables is positive, increase in one leads to increase in the other and vice versa. Also the value shows that the relationship is fairly strong.
Answer:
-6/8
Step-by-step explanation:
The slope formula is y2-y1
____
x2-x1
In the ordered pair (-20,4)
-20 is x1 the first x and 4 is x1
-12 is the x2 i.e. 2nd point and -10 is y2 i.e. 2nd point on y axis
so we plug in the value to the formula -10-(-4) two negatives become +
_____
-12-(-20)
so -10+4 -6 6
____ = ___ = - _
-12+20 8 8
(remember you subtract and the signs are different you subtract and use the sign of larger number)
Answer:

And the real value for this case is y=14. The residual is defined as:

Replacing we got:

And the best answer would be:
-2
Step-by-step explanation:
For this case we know that the best fit line for the relationship between x and y is given by:

And we know that an individual in the dataset has a score of 10 on the x-variable and a score of 14 on the y-variable. So then we can find the estimated value like this:

And the real value for this case is y=14. The residual is defined as:

Replacing we got:

And the best answer would be:
-2