Two fractions equivalent are 18/20 & 27/30
Step-by-step explanation:
Question no 1 ans is -10.
Question no 2 ans is 14.
Question no 3 ans is 7.
Question no 4 ans is 14.
If <em>x</em> + 1 is a factor of <em>p(x)</em> = <em>x</em>³ + <em>k</em> <em>x</em>² + <em>x</em> + 6, then by the remainder theorem, we have
<em>p</em> (-1) = (-1)³ + <em>k</em> (-1)² + (-1) + 6 = 0 → <em>k</em> = -4
So we have
<em>p(x)</em> = <em>x</em>³ - 4<em>x</em>² + <em>x</em> + 6
Dividing <em>p(x)</em> by <em>x</em> + 1 (using whatever method you prefer) gives
<em>p(x)</em> / (<em>x</em> + 1) = <em>x</em>² - 5<em>x</em> + 6
Synthetic division, for instance, might go like this:
-1 | 1 -4 1 6
... | -1 5 -6
----------------------------
... | 1 -5 6 0
Next, we have
<em>x</em>² - 5<em>x</em> + 6 = (<em>x</em> - 3) (<em>x</em> - 2)
so that, in addition to <em>x</em> = -1, the other two zeros of <em>p(x)</em> are <em>x</em> = 3 and <em>x</em> = 2
Using Visual inspection, the model which fits the data in the distribution better is the power function.
The power and linear functions can of the data can both be modeled using technology,
<u>Using Technology</u> :
The power function in the form 
which models the data is 
The linear function in the form 
which models the data is 
- Where A = intercept and B = slope
- From the model, correlation coefficient given by the power and linear models are 0.999 and 0.986 respectively.
- Hence, the power model is a better fit for the data than the linear model.
Therefore, Inspecting the models visually, the power function fits the data better as the points on the curve are closer to the regression line than on the linear model.
Learn more :brainly.com/question/18405415
$72 - $30 = $42
It increased $42.
Now take this number and divide by the original number (first):
42 ÷ 30
This is 1.4, let's convert this to a percentage.
We now times it by 100
1.4 × 100
The answer is 140%
