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2 years ago

-1/5y+7=7 What is the value of y?

1 answer:

8 0

The answer is y=0

See the attached photo for details

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Find the domain and range of the graph

Lostsunrise [7]

Answer:

The domain is -1 ≤x< 5

The range is -3≤y<3

Step-by-step explanation:

The domain is the values that x takes

The domain is -1 ≤x< 5

The range is the values that y takes

The range is -3≤y<3

6 0

2 years ago

A selective college would like to have an entering class of 950 students. Because not all students who are offered admission acc

pogonyaev

Answer:

a) The mean is 900 and the standard deviation is 15.

b) 100% probability that at least 800 students accept.

c) 0.05% probability that more than 950 will accept.

d) 94.84% probability that more than 950 will accept

Step-by-step explanation:

We use the normal approximation to the binomial to solve this question.

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 $\mu = E(X)$ , $\sigma = \sqrt{V(X)}$ .

(a) What are the mean and the standard deviation of the number X of students who accept?

$n = 1200, p = 0.75$ . So

$E(X) = np = 1200*0.75 = 900$

$\sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{1200*0.75*0.25} = 15$

The mean is 900 and the standard deviation is 15.

(b) Use the Normal approximation to find the probability that at least 800 students accept.

Using continuity corrections, this is $P(X \geq 800 - 0.5) = P(X \geq 799.5)$ , which is 1 subtracted by the pvalue of Z when X = 799.5. So

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

$Z = \frac{799.5 - 900}{15}$

$Z = -6.7$

$Z = -6.7$ has a pvalue of 0.

1 - 0 = 1

100% probability that at least 800 students accept.

(c) The college does not want more than 950 students. What is the probability that more than 950 will accept?

Using continuity corrections, this is $P(X \geq 950 - 0.5) = P(X \geq 949.5)$ , which is 1 subtracted by the pvalue of Z when X = 949.5. So

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

$Z = \frac{949.5 - 900}{15}$

$Z = 3.3$

$Z = 3.3$ has a pvalue of 0.9995

1 - 0.9995 = 0.0005

0.05% probability that more than 950 will accept.

(d) If the college decides to increase the number of admission offers to 1300, what is the probability that more than 950 will accept?

Now n = 1300. So

$E(X) = np = 1300*0.75 = 975$

$\sqrt{V(X)} = \sqrt{np(1-p)} = \sqrt{1200*0.75*0.25} = 15.6$

Same logic as c.

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

$Z = \frac{949.5 - 975}{15.6}$

$Z = -1.63$

$Z = -1.63$ has a pvalue of 0.0516

1 - 0.0516 = 0.9484

94.84% probability that more than 950 will accept

5 0

3 years ago

How does the experimental probability of choosing a yellow tile compare with the theoretical probability of choosing a yellow ti

Evgen [1.6K]

Answer:

The experimental probability is the same as the theoretical probability.

Step-by-step explanation:

The given data is:

color observed frequency relative frequency

Red 15 3/10

Blue 12 6/25

Green 8 4/25

Yellow 10 1/5

Purple 5 1/10

The experiment was repeated 50 numbers of times.

Solution:

Theoretical probability is basically what is expected to happen without experimenting and experimental probability is what actually happens as a results of an experiment.

Theoretical probability = favorable outcomes / all possible outcomes

Experimental probability = no. of times outcome occurs / no. of times

experiment is performed The experimental probability and theoretical probability are same i.e. 1/5

This can be seen from the table:

Experimental probability = 1/5

As the experiment is performed 50 times and the outcome (yellow tile) occurs 10 times so using the formula of experimental probability:

10/50 = 1/5

Now as given, there are 5 number of tiles (red,blue,green,yellow,purple) so number of possible outcomes is 5. Yellow tile among these 5 tiles is 1. So the favorable outcomes is 1. So looking at the given formula of theoretical probability:

1/5

experimental probability = 1/5

theoretical probability = 1/5

Hence the experimental probability is the same as the theoretical probability.

4 0

2 years ago

What percent is 300 of 1l

shusha [124]

Answer:

30%

Step-by-step explanation:

1L = 1000ml

--------------------

100%-> 1000

1%-> 10

300 ÷ 10 = 30%

7 0

3 years ago

What is the height of an airplane as it descends to an airport runway

stepladder [879]

The set of Real numbers consists of following sets:
- Rational numbers,
- Integers,
- Whole numbers.
And : R > I > W
The height of an airplane as it descends to an airport runway is in the whole numbers, rounded to the nearest 100 feet.
Answer: Whole number.

3 0

3 years ago