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zhannawk [14.2K]
2 years ago
9

Let E be the event where the sum of two rolled dice is greater than or equal to 7. List the outcomes in Ec.

Mathematics
1 answer:
zhenek [66]2 years ago
4 0

Answer:

(1, 1)  (1, 2)  (1, 3) (1,4)

(1,5)  (2,1)   (2,2) (2,3)

(2,4)  (3,1)  (3,2)   (3,3)

(4,1)   (4,2) (5,1)

Step-by-step explanation:

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H(x)=6 a linear function
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The vertex of the function’s graph is given. Find c. y = x2 + 10x + c; (-5, -27)
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5 0
3 years ago
Bro please help for a brainlist for best answer !!!!!!
tatiyna

The domain of a function are the possible input values of the function.

<em>The domain of the function is (d) Whole numbers</em>

First, we identify the start and end values of x on the graph.

We have:

Start = 0

The graph has no end; so:

End = \infty

This means that the domain of the graph is (0,\infty)

The number of times one can visit the pool cannot be decimal.

Hence, the domain of the function is whole numbers

Read more about domain at:

brainly.com/question/15339465

4 0
3 years ago
Suppose a research firm conducted a survey to determine the mean amount steady smokers spend on cigarettes during a week. A samp
shutvik [7]

Answer:

0.9910 = 99.10% probability that a sample of 170 steady smokers spend between $19 and $21

Step-by-step explanation:

To solve this question, we need to understand the normal probability distribution and the central limit theorem.

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the z-score 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 p-value, we get the probability that the value of the measure is greater than X.

Central Limit Theorem

The Central Limit Theorem estabilishes that, for a normally distributed random variable X, with mean \mu and standard deviation \sigma, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean \mu and standard deviation s = \frac{\sigma}{\sqrt{n}}.

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

Mean of 20, standard deviation of 5:

This means that \mu = 20, \sigma = 5

Sample of 170:

This means that n = 170, s = \frac{5}{\sqrt{170}}

What is the probability that a sample of 170 steady smokers spend between $19 and $21?

This is the p-value of Z when X = 21 subtracted by the p-value of Z when X = 19.

X = 21

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

By the Central Limit Theorem

Z = \frac{X - \mu}{s}

Z = \frac{21 - 20}{\frac{5}{\sqrt{170}}}

Z = 2.61

Z = 2.61 has a p-value of 0.9955

X = 19

Z = \frac{X - \mu}{s}

Z = \frac{19 - 20}{\frac{5}{\sqrt{170}}}

Z = -2.61

Z = -2.61 has a p-value of 0.0045

0.9955 - 0.0045 = 0.9910

0.9910 = 99.10% probability that a sample of 170 steady smokers spend between $19 and $21

3 0
3 years ago
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