Y=3x^2+11x-4 and y=10x-1. solve the system of equations

What is the equation in slope-intercept form of the line that passes through the points(-4,2) and (12,6)?

aleksandrvk [35]

Answer:

y=1/4x+3

Step-by-step explanation:

m=(y2-y1)/(x2-x1)

m=(6-2)/(12-(-4))=4/(12+4)=4/16=1/4

y-y1=m(x-x1)

y-2=1/4(x-(-4))

y-2=1/4(x+4)

y=1/4x+4/4+2

y=1/4x+1+2

y=1/4x+3

3 0

2 years ago

A survey of 260 families show that 99 had dog 76 had cat 34 had dog and cat 98 had neither a cat nor a dog nor a parakeet 8 had

Archy [21]

Answer:

Option D. 21

Step-by-step explanation:

The question is as shown in the attached figure 1

The Venn diagram representing the problem is the attached figure 2

D ⇒ Dog , C⇒ Cat and P ⇒ parakeet

Let the The families had parakeet only = X

A survey of 260 families show that:

99 had dog

76 had cat

34 had dog and cat

98 had neither a cat nor a dog nor a parakeet

8 had a cat a dog and a parakeet

So,

The families had a dog and a cat only = 34 - 8 = 26

The families had a dog only = 99 - (26 + 8 ) = 65

The families had a cat only = 76 - (26 + 8) = 42

∴ X = 260 - ( 98 + 8 + 26 + 65 + 42 ) = 260 - 239 = 21

So, The families had a parakeet only = 21

The answer is option D

5 0

2 years ago

The amount people who pay for cell phone service varies quite a bit, but the mean

melamori03 [73]

Answer:

a) The mean is $55 and the standard deviation is $0.6957

b) The shape of the sampling distribution of x is approximately normal.

c) 0.0749 = 7.49% probability that the average cell phone service paid by the sample of cell phone users will exceed $56.

Step-by-step explanation:

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 $s = \sqrt{\frac{p(1-p)}{n}}$