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rodikova [14]
3 years ago
14

14/100 simplest form

Mathematics
2 answers:
Lorico [155]3 years ago
7 0
14/100
= (14/2) / (100/2)
= 7/50

14/100 in its simplest form is 7/50~
Over [174]3 years ago
3 0
14/100 in simplest form is 7/50 

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Converting 7/8 to a decimal.
Elza [17]
Ok, so if you want to convert 7/8 into a decimal, you just simply divide 7 into 8.  Well that should be 0.875 because 7 ÷ 8 = 0.875 Hope that helped!!!  :)
5 0
3 years ago
Read 2 more answers
Who can help me with this entire page?
trasher [3.6K]

Answer:

I'm not entirely sure what the question is but every thing under 12.5 is closer to 12, everything 12.5 and upwards like 12.87 would be closer to 13

8 0
2 years ago
Tan 1.1 – tan 4.6/
VladimirAG [237]

The value of the given equation is –0.37458.

Solution:

Given equation is:

$\frac{\tan 1.1-\tan 4.6}{1+\tan 1.1 \tan 4.6}

Let us first find the values.

The value of tan 1.1 = 1.96475

The value of tan 4.6 = 8.86017

Substitute these values in the given equation.

$\frac{\tan 1.1-\tan 4.6}{1+\tan 1.1 \tan 4.6}

            $=\frac{1.96475-8.86017}{1+1.96475 \times 8.86017}

            $=\frac{-6.89542}{1+17.4080}

            $=\frac{-6.89542}{18.4080}

            = –0.37458

$\frac{\tan 1.1-\tan 4.6}{1+\tan 1.1 \tan 4.6}=-0.37458

Hence the value of the given equation is –0.37458.

7 0
3 years ago
A regular stained glass window is 2 feet by 4 feet. A clear glass border is constructed around the stained glass window. The wid
alexira [117]
Let x = width of border

Area is given to be 7 square feet or 49.

49 = (2x + 2)(2x + 4)

Solve for x.

6 0
3 years ago
Recall the Akaike information Criterion (AIC) as well as the related Bayesian Information Criterion (BIC) from our study of Vari
irga5000 [103]

Step-by-step explanation:

To check out how efficient or accurate a model is, we use the akaike information criterion or the Bayesian. If the AIC or BIC are lower, then this model would be better. They are also used to control for model complexity

Akaike information criterion = 2k-2ln where k is the number of parameter. A higher k gives a higher AIC.

In the real world complex models are discouraged and avoided since

1. They cause data to be over fitted and can capture noise and information from this data.

2. They are complex and therefore difficult to interpret

3. They consume a lot of time and computing them has several inefficiencies.

Using these two as measure of performance, we can select optimal choice of independent variable.

With forward/backward regression, we are able to put new variables in the model or remove from it. The best is the one with lowest AIC.

5 0
3 years ago
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