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2 years ago

Will your career more important than anything else

2 answers:

7 0

Well, sometimes, it will. You know, cause nowadays everything in this world, even the people, will judge you based on how you doing on your life. Or maybe some people will only care about you because of your occupation and what do you have. But, for me, what is the meaning of life if you didn’t experience any happiness, love, or anything in your life? For example, it is your career more important than your family? Is it important than your happiness in your life? So, for me, career is not so important. I mean, yes with it you can earn money. But sometimes, money can’t bring happiness to us.

Lisa [10]2 years ago

5 0

Honestly, it depends on what you most value in life, wether it be your career, love life, family, etc.

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Which of the following numbers<br> is a solution to this inequality?<br> 14x > 36<br> 3<br> 2.

Setler79 [48]

Answer:

$x=\frac{18}{7}$

Step-by-step explanation:

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2 years ago

Hillary, Meredith, and Aly are sitting in their favorite coffee shop when their waiter asks: "Does everyone want coffee?" Hillar

liraira [26]

Answer:

a) Yes.

b) Yes.

Step-by-step explanation:

Meredith and Hillary both want coffe, but they don't know if the other two people do, therefore they can't know if everyone want coffee. If they didn't want coffee, their answer would have been just "no".

Aly knows that she doesn't want coffee, therefore she knows that not everyone wants coffee.

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2 years ago

Laticia randomly selected 25% of the seventh grade students in her school and asked them their favorite season. Of the students

Marysya12 [62]

I would say 75 or 150
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2 years ago

Please help me and ill mark you as brainlest ;)!

JulsSmile [24]

The hypotenuse would be 9 inches as 6 is equal to 2/3 of 9 :)

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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).

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3 years ago