Part A
<h3>Answer:
h^2 + 4h</h3>
-------------------
Explanation:
We multiply the length and height to get the area
area = (length)*(height)
area = (h+4)*(h)
area = h(h+4)
area = h^2 + 4h .... apply the distributive property
The units for the area are in square inches.
===========================================================
Part B
<h3>Answer:
h^2 + 16h + 60</h3>
-------------------
Explanation:
If we add a 3 inch frame along the border, then we're adding two copies of 3 inches along the bottom side. The h+4 along the bottom updates to h+4+3+3 = h+10 along the bottom.
Similarly, along the vertical side we'd have the h go to h+3+3 = h+6
The old rectangle that was h by h+4 is now h+6 by h+10
Multiply these expressions to find the area
area = length*width
area = (h+6)(h+10)
area = x(h+10) ..... replace h+6 with x
area = xh + 10x .... distribute
area = h( x ) + 10( x )
area = h( h+6 ) + 10( h+6 ) .... plug in x = h+6
area = h^2+6h + 10h+60 .... distribute again twice more
area = h^2 + 16h + 60
You can also use the box method or the FOIL rule as alternative routes to find the area.
The units for the area are in square inches.
Its proportional.
(I need 20 characters but thats all really.)
Answer:
<u>1/7=3/21</u>
<u>7/1=21/3</u>
the other fractions are not correct/valid therefore the fractions above are the correct answers
Step-by-step explanation:
Let me know if you need any other help:)
<span>1. </span>When given a raw score, it must be converted
into a z-score (standard score). Raw scores cannot be placed on a normal
distribution curve because they do not have the same means and standard
deviations, but when it is converted into a z-score, the number of standard
deviations above or below the population mean can be measured. The z-scores on
the center are average, the scores on the left are lower than average and the
scores on the right are higher than average.
<span>2. </span>A z-score is a standard score which can be
placed on a normal distribution curve. A z-score indicates the distance of the
standard deviations from the mean (center of the curve).
