Step-by-step explanation:
Regression analysis is used to infer about the relationship between two or more variables.
The line of best fit is a straight line representing the regression equation on a scatter plot. The may pass through either some point or all points or none of the points.
<u>Method 1:</u>
Using regression analysis the line of best fit is: 
Here <em>α </em>= intercept, <em>β</em> = slope and <em>e</em> = error.
The formula to compute the intercept is:

Here<em> </em> and
 and  are mean of the <em>y</em> and <em>x</em> values respectively.
 are mean of the <em>y</em> and <em>x</em> values respectively.

The formula to compute the slope is:

And the formula to compute the error is:

<u>Method 2:</u>
The regression line can be determined using the descriptive statistics mean, standard deviation and correlation.
The equation of the line of best fit is:

Here <em>r</em> = correlation coefficient = 
 and
 and  are standard deviation of <em>x</em> and <em>y</em> respectively.
 are standard deviation of <em>x</em> and <em>y</em> respectively.

 
        
             
        
        
        
Answer:
 153.86
Step-by-step explanation:
formula - A = π × r2
3.14 x 7^2
= 153.86
 
        
             
        
        
        
Answer:
W=1000C/tc
Step-by-step explanation:
First multiply both side 1000: 1000C=Wtc
Divide both side by tc: 1000C/tc=W (t, c ≠0)
 
        
             
        
        
        
23958
29538
25398
25938
29358
23598
 I think this is what you meant.
        
             
        
        
        
Answer:
B:
Step-by-step explanation: