The correlation is a negative correlation, because weights and city MPG do not increase at the same time
<h3>The graph of the table of values</h3>To graph of the table of values, we plot
- The weights on the x-axis
- The city MPG on the y-axis
See attachment for graph
<h3>Type of correlation</h3>The correlation is a negative correlation, because weights and city MPG do not increase at the same time
<h3>The equation of the line of best fit</h3>To do this, we make use of a graphing calculator.
From the graphing calculator, we have the following summary:
- Sum of X = 463
- Sum of Y = 388
- Mean X = 28.9375
- Mean Y = 24.25
- Sum of squares (SSX) = 862.9375
- Sum of products (SP) = -857.75
The line of best fit equation is
y = bx + a
Where
b = SP/SSX = -857.75/862.94 = -0.99
a = MY - bMX = 24.25 - (-0.99*28.94) = 53.0
So, we have:
y = -0.99x + 53
Hence, the equation of the line of best fit is y = -0.99x + 53
<h3>The weight for 30 MPG</h3>This means that y = 30
So, we have:
-0.99x + 53 = 30
Subtract 53 from both sides
-0.99x = -23
Divide by -0.99
x =23
Hence, the predicted weight is 23 pounds
<h3>The city MPG for 1500 pounds</h3>This means that x = 1500
So, we have:
y = -0.99 * 1500 + 53
Evaluate
y = -1432
Hence, the city MPG for 1500 pounds is -1432
Read more about linear regression at:
#SPJ1
