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3 years ago

URGENT, ALL HELP ACCEPTED PLEASE! Solve y= 3x-1 and (1/2)y+x=1 for their COMMON solution.

1 answer:

6 0

Simplify the second equation.

1/2y = -x + 1

Multiply both sides by 2

y = -2x + 2

Since both equations equal y you can set them equal to each other.

-2x + 2 = 3x - 1

Solve for X

-5x = -3

x = 3/5

Plug this into one of the equations.

3(3/5) - 1 = y

1.8 - 1 = y

y = .8

(0.6, 0.8)

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The sum of three consecutive multiples of 3 is equal to 6 more than four times the smallest multiple. What is the largest multip

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Answer: (a) 9

<u>Step-by-step explanation:</u>

1st multiple of 3: 1(3x)

2nd multiple of 3: 2(3x)

3rd multiple of 3: 3(3x)

Sum = 4(1st multiple of 3) + 6

1(3x) + 2(3x) + 3(3x) = 4(3x) + 6

3x + 6x + 9x = 12x + 6

18x = 12x + 6

6x = 6

x = 1

Largest (3rd) multiple is: 3(3x)

= 9x

= 9 · 1

= 9

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3 years ago

Read 2 more answers

According to General Social Survey of 2016, the population distribution of number of years of education for self-employed indivi

nikdorinn [45]

Answer:

a) Mean is 12.9

b) Standard Error

i) n = 16, Standard Error = 1

The shape of the sampling distribution means is not normal

ii) n = 49 , Standard Error = 0.5714285714

The shape of the sampling distribution means is normal

iii) n = 121, Standard Error = 0.3636363636

The shape of the sampling distribution means is normal

c)Describe the pattern as n increases

As the number of random samples(n) increases the value for the standard error decreases

Step-by-step explanation:

Central Limit Theorem states that

if the sample size is large (generally n ≥ 30), and the standard deviation of the population is finite, then the distribution of sample means will be approximately normal.

a) 16 residents

Mean = 12.9

Standard Error = Standard Deviation /√n

= 4/√16

= 4/4

= 1

n < 30, hence, The shape of the sampling distribution means is not normal

b) 49 residents

= Mean = 12.9

Standard Error = Standard Deviation /√n

= 4/√49

= 4/7

= 0.5714285714

n > 30, hence, The shape of the sampling distribution means is normal

c) 121 residents

Mean = 12.9

Standard Error = Standard Deviation /√n

= 4/√121

= 4/11

= 0.3636363636

n > 30, hence, The shape of the sampling distribution means is normal

Describe the pattern as n increases

As the number of random samples(n) increases the value for the standard error decreases

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3 years ago

Two real-valued functions, f(x) and g(x), are defined as f(x) = x2 + 6x + 9 and g(x) = x2 – 9. Find the results of combining the

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I hope this helps you

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3 years ago

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Answer:

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3 years ago

A Government company claims that an average light bulb lasts 270 days. A researcher randomly selects 18 bulbs for testing. The s

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Answer:

31.92% probability that 18 randomly selected bulbs would have an average life of no more than 260 days

Step-by-step explanation:

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

Normal probability distribution

When the distribution is normal, we use 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.

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.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean $\mu = p$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}}$