Asssssssssaaaaaappppppppp

Mathematics

1 answer:

BigorU [14]2 years ago

7 0

Answer:

Step-by-step explanation:

Just multiply all numbers together.

Plz give me brainliest

You might be interested in

What power or what 10 does that equal

myrzilka [38]

A power of 10 is as many number 10s as indicated by exponent multiplied together shown in a long form a power if 10 is the number 1 followed by zeros example:10^6 is written 1,000,000

4 0

2 years ago

Read 2 more answers

Blake and 3 friends meet for lunch . his

____ [38]

Answer:

if this is finish the problem then

"his friends decided to order pizza for lunch. one of his friends said they wanted to eat 5 slices. the other one said he wanted 3 and the last one said they must wanted 7 while little Blake just wanted 2. how many boxes of pizza would Blake have to order."

MY answer: zero because Blake made them pay for their own boxes. they didn't want to at first but then they saw the knife Blake was holding in his hand and decide that if they want to live they must buy their own pizza and give him some or theirs

7 0

3 years ago

Read 2 more answers

"is it appropriate to use the normal approximation for the sampling distribution of"

Katyanochek1 [597]

Answer: Normal approximation can be used for discrete sampling distributions, such as Binomial distribution and Poisson distribution if certain conditions are met.

Step-by-step explanation: We will give conditions under which the Binomial and Poisson distribitions, which are discrete, can be approximated by the Normal distribution. This procedure is called normal approximation.

1. Binomial distribution: Let the sampling distribution be the binomial distribution $B(n,p)$ , where $n$ is the number of trials and $p$ is the probability of success. It can be approximated by the Normal distribution with the mean of $np$ and the variance of $np(1-p)$ , denoted by $N(np,np(1-p))$ if the following condition is met:

$n>9\left(\frac{1-p}{p}\right)\text{ and } n>9\left(\frac{p}{1-p}\right)$

2. Poisson distribution: Let the sampling distribution be the Poisson distribution $P(\lambda)$ where $\lambda$ is its mean. It can be approximated by the Normal distribution with the mean $\lambda$ and the variance $\lambda$ , denoted by $N(\lambda,\lambda)$ when $\lambda$ is large enough, say $\lambda>1000$ (however, different sources may give different lower value for $\lambda$ but the greater it is, the better the approximation).