Method 1:
4(754)
=4(700+50+4)
=2800 + 200 + 16
=3000+16
=3016
-----------------
Method 2:
4(754)
=4(250+250+250+4)
=1000+1000+1000+16
=3016
Answer:
Step-by-step explanation:
If 7.5 % has green eyes, then 92.5% (the complement given by 100%-7.5%) dont have green eyes. 92.5% of 120 is given by
0.925*(120)=111
111 students in the grade dont have green eyes.
Well, we could try adding up odd numbers, and look to see when we reach 400. But I'm hoping to find an easier way.
First of all ... I'm not sure this will help, but let's stop and notice it anyway ...
An odd number of odd numbers (like 1, 3, 5) add up to an odd number, but
an even number of odd numbers (like 1,3,5,7) add up to an even number.
So if the sum is going to be exactly 400, then there will have to be an even
number of items in the set.
Now, let's put down an even number of odd numbers to work with,and see
what we can notice about them:
1, 3, 5, 7, 9, 11, 13, 15 .
Number of items in the set . . . 8
Sum of all the items in the set . . . 64
Hmmm. That's interesting. 64 happens to be the square of 8 .
Do you think that might be all there is to it ?
Let's check it out:
Even-numbered lists of odd numbers:
1, 3 Items = 2, Sum = 4
1, 3, 5, 7 Items = 4, Sum = 16
1, 3, 5, 7, 9, 11 Items = 6, Sum = 36
1, 3, 5, 7, 9, 11, 13, 15 . . Items = 8, Sum = 64 .
Amazing ! The sum is always the square of the number of items in the set !
For a sum of 400 ... which just happens to be the square of 20,
we just need the <em><u>first 20 consecutive odd numbers</u></em>.
I slogged through it on my calculator, and it's true.
I never knew this before. It seems to be something valuable
to keep in my tool-box (and cherish always).
Answer:
7
4
Step-by-step explanation:
The <u>actual values</u> are shown on the given graph as <u>blue points</u>.
The <u>line of regression</u> is shown on the given graph as the <u>red line</u>.
From inspection of the graph, in the year 2000 the actual rainfall was 43 cm, shown by point (2000, 43). It appears that the regression line is at y = 50 when x is the year 2000.
⇒ Difference = 50 - 43 = 7 cm
<u>In 2000, the actual rainfall was </u><u>7</u><u> centimeters below what the model predicts</u>.
From inspection of the graph, in the year 2003 the actual rainfall was 44 cm, shown by point (2003, 40). It appears that the regression line is at y = 40 when x is the year 2003.
⇒ Difference = 44 - 40 = 4 cm
<u>In 2003, the actual rainfall was </u><u>4</u><u> centimeters above what the model predicts.</u>
