Can someone please tell me the steps to find a number four?

Mathematics

2 answers:

Delicious77 [7]3 years ago

5 0

The answer is 21.
I am not sure if you're looking for the answer, or the steps... get back to me foor help.

ki77a [65]3 years ago

5 0

21 is correct I hope you pass

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Look at the graph shown:

NNADVOKAT [17]

We are going to base the answer off of the y=mx+b form where m represents slope and b represents the y-intercept.

First, we know that b must be -1 because the line hits the y-axis when y is -1
So this leaves us with either the first or second choice

Then we choose two points to find the slope. I am using (0,-1) and (1,2). If you count the boxes, the y-value increases by 3 as the x-value increases by 1. So the slope is 3/1 or 3.

So then we know the answer is y=3x-1

Hope this helps

4 0

3 years ago

An Epson inkjet printer ad advertises that the black ink cartridge will provide enough ink for an average of 245 pages. Assume t

Neko [114]

Answer:

35.2% probability that the sample mean will be 246 pages or more

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