Correctly compare the numbers. 0.9 1.1 1. = 2. < 3. >

Mathematics

1 answer:

creativ13 [48]3 years ago

6 0

Answer:

2. <

Step-by-step explanation:

A units digit of 0 is less than a units digit of 1, so ...

0.9 < 1.1

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The volume of a cylinder is 252π252π cm3 and its height is 7 cm.

kirill [66]

V = (pi) * r^2 * h
h = 7
V = 252(pi)

252(pi) = r^2 * 7
252(pi) / 7 = r^2
36(pi) = r^2
sqrt 36(pi) = r
6 = r <==== radius is 6 cm

8 0

3 years ago

"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).