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3 years ago

What is the distance between -4 and -14

Mathematics

2 answers:

____ [38]3 years ago

6 0

Answer:

Step-by-step explanation:

Since they are both negative you just count the distance between them like literally:

Absolute value of 4 is 4

Absolute value of 14 is 14

14 - 4 = 10

Sidana [21]3 years ago

3 0

The distance between -14 and -4 is 10. since they are both negative numbers, you just have to find the different between 14 and 4 which is 10.

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the city of James town is 2 meters below sea level. Takoradi, a city in western region, is 7 meters below sea level . How much h

never [62]

Answer:

James town is 5 meters higher than Takoradi .

Step-by-step explanation:

Given:

Height of James town = 2 meters below sea level

Height of Takoradi town = 7 meters below sea level

To find:

How much higher is James town that Takoradi = ?

Solution:

As we can see the standard of height is how much the town is below the sea level.

So, the height of town having lesser value will be at a higher level.

Value of Height of James town is lesser than that of Takoradi town.

Therefore, James town is at a higher level.

Difference of height = 7 meters - 2 meters = 5 meters

So, the answer is:

James town is 5 meters higher than Takoradi.

8 0

2 years ago

Write an equivalent expression by distributing the "-−" sign outside the parentheses: -(3.4p-6q+6) −(3.4p−6q+6)

julia-pushkina [17]

Answer:

$-(3.4p-6q+6)$ = $-3.4p+6q-6$

Step-by-step explanation:

Given

$-(3.4p-6q+6)$

Required

Simplify

$-(3.4p-6q+6)$

Rewrite as

$-1(3.4p-6q+6)$

$-1 * (3.4p-6q+6)$

Open the bracket

$-3.4p+6q-6$

7 0

2 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).