All categories

3 years ago

What is the image of 4,3 reflected across the Y axis

Mathematics

1 answer:

puteri [66]3 years ago

6 0

Answer:

(-4 , 3)

Step-by-step explanation:

(x,y) reflected over y axis ---> (-x,y)

You might be interested in

Y MORE THAN 4 is -36 translate for me please into math symbols then solve problem (list steps)

Sphinxa [80]

$y + 4 = -36

Subtract 4 both sides.

y = -40

Check solution. 

-40 + 4 = -36

This is correct.

You're welcome. 
$ Observe below please.

4 0

3 years ago

8 divided by 2 (2+2). 1 or 16

laiz [17]

Answer:

Step-by-step explanation:

$8/2(2+2)$

Following the order of operations (PEMDAS), combine the terms in your parentheses:

$8/2(4)$

Remember that we follow the order of operations from left to right.

Divide 8 into 2:

$4(4)$

Multiply:

$16$

8 0

3 years ago

Pls answer 2 people or more

fredd [130]

I believe it’s B . Not 100 percent sure but yeah

6 0

2 years ago

Because not all airline passengers show up for their reserved seat, an airline sells 125 tickets for a flight that holds only 12

melamori03 [73]

Answer:

98.75% probability that every passenger who shows up can take the flight

Step-by-step explanation:

For each passenger who show up, there are only two possible outcomes. Either they can take the flight, or they do not. The probability of a passenger taking the flight is independent from other passenger. So the binomial probability distribution is used to solve this question.

However, we are working with a large sample. So i am going to aproximate this binomial distribution to the normal.

Binomial probability distribution

Probability of exactly x sucesses on n repeated trials, with p probability.

Can be approximated to a normal distribution, using the expected value and the standard deviation.

The expected value of the binomial distribution is:

$E(X) = np$

The standard deviation of the binomial distribution is:

$\sqrt{V(X)} = \sqrt{np(1-p)}$

Normal probability distribution

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

When we are approximating a binomial distribution to a normal one, we have that $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .