Type an equation for the following pattern! Please Help!!!

Mathematics

1 answer:

Helga [31]3 years ago

6 0

Answer:

y=x+2

Step-by-step explanation:

1) Solve for m using the equation m=y2-y1/x2-x1 by plugging in any 2 coordinates from the table

2) After getting m, which is 1, you can solve for b by plugging in another coordinate. For example,the coordinate (1,3): 3=(1)1+b

3) You then solve for b, which is 2

Answer: y=x+2

You might be interested in

Find the distance between the points (5, -5) and (-7,4).

abruzzese [7]

Answer:

<h2>The answer is 15 units</h2>

Step-by-step explanation:

The distance between two points can be found by using the formula

$d = \sqrt{ ({x1 - x2})^{2} + ({y1 - y2})^{2} } \\$

where

(x1 , y1) and (x2 , y2) are the points

From the question the points are

(5, -5) and (-7,4)

The distance between them is

$d = \sqrt{ ({5 + 7})^{2} + ({ - 5 - 4})^{2} } \\ = \sqrt{ {12}^{2} + ( { - 9})^{2} } \\ = \sqrt{144 + 81} \\ = \sqrt{225} \\ = 15 \: \: \: \: \: \:$

We have the final answer as

<h3>15 units</h3>

Hope this helps you

4 0

3 years ago

The amounts of nicotine in a certain brand of cigarette are normally distributed with a mean of 0.895 g and a standard deviation

kvasek [131]

Answer:

3.67% probability of randomly seleting 37 cigarettes with a mean of 0.809 g or less.

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 normally distributed samples are solved using 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 $s = \frac{\sigma}{\sqrt{n}}$ .