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Tanzania [10]
3 years ago
5

How can you solve the equation 4x= 2X-2 graphically?

Mathematics
2 answers:
Vanyuwa [196]3 years ago
4 0
This is 4x=2x-2 as a graph

Ghella [55]3 years ago
4 0
-2 is the y intercept meaning you need to graph the -2 on the y axis. Then for the slope, it is m in the mx which is 2. So you graph left or right. It’s basically rise over run
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What happens when you get a negative square root in the quadratic formula?
prisoha [69]
Edited : I apologise I misunderstood the question.

You can solve the equation.
7 0
3 years ago
Can you please help me answer this​
lesya692 [45]

9514 1404 393

Answer:

  (a)  Not congruent

Step-by-step explanation:

Angles are congruent, which means the triangles are <em>similar</em>. We need to know at least one pair of corresponding sides is congruent in order to say the triangles are congruent. No sides are marked, so we must conclude ...

  Not Congruent

8 0
2 years ago
While waiting for a bus, Todd decided to play with consecutive numbers (whole numbers that increase in order without skipping, s
Lesechka [4]

Answer:

A: 8+9+10=27

   9+10+11=30

   10+11+12=13

B: 19+20+21

C:  There isn't any.

Step-by-step explanation:

It just is lol.

4 0
3 years ago
A game is played with a spinner on a circle, like the minute hand on a clock. The circle is marked evenly from 0 to 100, so, for
zheka24 [161]

Answer:

The probability is 1/2

Step-by-step explanation:

The time a person is given corresponds to a uniform distribution with values between 0 and 100. The mean of this distribution is 0+100/2 = 50 and the variance is (100-0)²/12 = 833.3.

When we take 100 players we are taking 100 independent samples from this same random variable. The mean sample, lets call it X, has equal mean but the variance is equal to the variance divided by the length of the sample, hence it is 833.3/100 = 8.333.

As a consecuence of the Central Limit Theorem, the mean sample (taken from independant identically distributed random variables) has distribution Normal with parameters μ = 50, σ= 8.333. We take the standarization of X, calling it W, whose distribution is Normal Standard, in other words

W = \frac{X - \mu}{\sigma} = \frac{X - 50}{8.333} \simeq N(0,1)

The values of the cummulative distribution of the Standard Normal distribution, lets denote it \phi , are tabulated and they can be found in the attached file, We want to know when X is above 50, we can solve that by using the standarization

P(X > 50) = P(\frac{X-50}{8.33} > \frac{50-50}{8.33}) = P(W > 0) = \phi(0) = 1/2

Download pdf
8 0
3 years ago
What is the 57th term of the arithmetic sequence : 11,8,5,2
andriy [413]
I think its this <span> 14 - 3*57 = 14 - 171 = -157 </span>
4 0
3 years ago
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