2560-1944= 616gallons
7 days in a week or 14 days in two weeks
616gallons / 14days = 44 gallons / 1 day
Notice in the fraction we have
(Gallons / days)
Now if you filled the take up the entire way
2560 gallons
We have gallons and the question wants the amount of days
Thus to cancel gallons we set the equation up as such
(2560 gallons) x (1 day / 44 gallons) = 58.18 days
Or 58 days
59,317 I dno how to explain it but it may be wrong you should do the math yourself to check..
<span>f(x) = x</span>² <span>+ 12x + 6 </span>→ y = x² + 12x + 6<span>
Let us convert the standard form into vertex form.
1) Complete the squares. Isolate x</span>² and x terms.
<span>y - 6 = x</span>² + 12x
<span>
2) Create the perfect square trinomial. Whatever number is added on one side must also be added on the other side.
y - 6 + 36 = x</span>² + 12x + 36<span>
y + 30 = (x + 6)</span>²
<span>y = (x + 6)</span>² - 30 ← Vertex form
<span>
To check:
y = (x + 6) (x + 6) - 30
y = x</span>² + 6x + 6x + 36 - 30
<span>y = x</span>² + 12x + 6<span>
The zero that could be added to the given function is 36, -36</span>
Answer:
Convert the meters to millimeters
1m = 1000mm
6m = 6000mm
40mm represents 6000mm
Find the scale factor
6000/40 = 150
This means 40 * 150 = 6000
Yup find what 50mm represents:
50 * 150 = 7500
7500mm
7.5m
Answer with explanation:
A salesperson can use probability to get an idea of his business as using probability he can estimate his sale of the next month as well, based on the present and previous months sales.
It can help him sort issues or errors he is facing in his business as he will get a complete idea of his business using probability.
Moreover, he can forecast future sales by using a technique which involves assigning percentages or weighting benchmarks in sales cycle, so that he can estimate the expected revenue generated.
For example:
A supermarket sales person can assign probabilities to benchmarks in sale cycle as providing needs analysis (25 % probability), adding new product (50%Probability) , Remove a product ( 75 % probability), closing sale (100% Probability) . If these probabilities are large, then forecast model can be objective.
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So just like that by assigning probabilities to benchmarks, a sales person can forecast future sales
