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Tamiku [17]
3 years ago
7

Pls…… HELPPPP I have no clue what I’m doing

Mathematics
1 answer:
vova2212 [387]3 years ago
5 0

Answer:

x = 4 and y = 8.

Step-by-step explanation:

The given equations are :

-8x+y=-24 ....(1)

and

3x-2y=-4 .....(2)

Multiplying equation (1) by 2.

-16x+2y=-48 ....(3)

Adding equation (2) and (2).

3x-2y+(-16x+2y) = -4-48

3x-16x= -52

-13x = -52

x = 4

Put the value of x in equation (1)

-8(4)+y=-24

-32 + y = -24

y = -24+32

y = 8

Hence, the solutions of the equations are x = 4 and y = 8.

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harina [27]

Maybe the Answer is B.

B.) 0.03%

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3 years ago
Find the gradient of the line l1 which has equation 4x-3y+5=0 .
Nikitich [7]

Answer:

The gradient is the same as the slope. To find the slope, let's convert this from standard form to slope-intercept form.

4x - 3y + 5 = 0

4x + 5 = 3y

4/3x + 5/3 = y therefore the answer is 4/3.

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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

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