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oee [108]
3 years ago
5

Paco deconstructs this isosceles trapezoid to find the area.

Mathematics
2 answers:
Lina20 [59]3 years ago
6 0
It would be the second one!!!
8090 [49]3 years ago
3 0
I’m pretty sure it is the second one
Hope this helps
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Ms. Ramirez has a class of 15 students. She can spend $18 on each student to buy math supplies for the year. She first buys all
Aloiza [94]

Answer:7.775

Step-by-step explanation:

So u do 130.05 ÷18 =7.225

Now u do 15 - 7.225 = 7.775

7.775 is the money she can still spend for them.

Also u could do 15 x 18 = 270

270 ÷ 2 = 135

8 0
3 years ago
you must attend a minimum of 85% of the practices in order to play in the playoffs you have made 37 of the 42 practices will you
Deffense [45]
Yes, you'd be able to play.
37/42 = .88 = 88%
So you've attended more than 85% of the practices.
3 0
3 years ago
I have way more questions than this answer them if you want pleaseee!!
aliina [53]

The right answer is Option C.

Step-by-step explanation:

Given inequality is

6(2x-1)  > 24

Solving the inequality

6*2x-1*6>24\\12x-6>24

Adding 6 on both sides

12x-6+6>24+6\\12x>30

Dividing both sides by 12

\frac{12x}{12}>\frac{30}{12}\\x>\frac{5}{2}

Therefore,

x>\frac{5}{2}

The right answer is Option C.

Keywords: inequality, division

Learn more about division at:

  • brainly.com/question/106975
  • brainly.com/question/107042

#LearnwithBrainly

5 0
3 years ago
1 A baseball is struck such that its position on a plane perpendicular to home plate can be described by the equation y = (x - 1
marshall27 [118]

Answer:

21

Step-by-step explanation:

7 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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