We start with

Next, we can factor out the term on the right side


Now, we will substitute back
resulting in
So,
.............Response
Honestly, I find Mrs. Garcia's method easier to perform mentally. It hinges on how familiar you are with your multiples of 5. (5*15 = 75 is a multiplication I often use)
Melissa's approach involves calculating 5*20 = 100 and 5*9 = 45, then combines the 3-digit result 100 with the 2-digit result 45, yielding 145. Adding 45 to 00 is simple and doesn’t require carrying digits, thus the arithmetic is fairly straightforward.
Mrs. Garcia's technique involves computing 5*14 = 70 and 5*15 = 75, then summing these two-digit results. Many people may not readily recall that 5*15=75, which complicates forming that product. The addition of 70 and 75 requires a carrying operation, making the math somewhat more complex. The resulting total is 145.
(The rationale behind my preference for Mrs. Garcia's method is that I can achieve the final sum by simply doubling 7 tens, followed by adding 5. The only 3-digit number to remember mentally is the ultimate total.)
_____Subtraction introduces a slight complication, yet reshaping it as $5(30 -1) = $150 - 5 = $145 is possible.
Or, you may reframe it as $5(28 +1) = $140 +5 = $145.
Dividing an even number by 2 to find the product of 5 is straightforward when you append a zero.
5*14 = 10*7 = 70
5*28 = 10*14 = 140.
I think it’s 156 hundreds, 3 tens, and 8 ones.
Answer:
The regression line is not an appropriate model due to the existence of a pattern in the residual plot.
Step-by-step explanation:
A residual plot has been provided for a certain data set.
The residual plot indicates a scatter relationship between x and y.
The plotted points demonstrate that a linear relation is unlikely; it appears to be more parabolic or exponential in nature.
This suggests the regression line is not a suitable model as the residuals do not converge towards 0.
Additionally, a linear trend pattern is absent.
D) The regression line is not a suitable model as it exhibits a pattern in the residual plot.