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2 years ago

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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I wanna buy 3/8 a pound of Swiss cheese and 1/4 pound of American cheese.which pairs of fractions are equivalent to the amount a

Diano4ka-milaya [45]

B, and D i think is right

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3 years ago

H(x)=6 a linear function

shusha [124]

Yes, this is a constant function. This means that f(x) = c (c is a constant function) so no matter what the input is for h(x)=6 is, the output will be 6. Therefore this is a straight line with a slope of 0 and thus a linear function.

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2 years ago

The vertex of the function’s graph is given. Find c. y = x2 + 10x + c; (-5, -27)

castortr0y [4]

Actually I didn't see the (-5, -27), the answer would be -2.

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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 $s = \frac{\sigma}{\sqrt{n}}$ .