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3 years ago

Kian has been asked to create a company logo to be put on all company merchandise. The logo needs to be

Mathematics

1 answer:

Sladkaya [172]3 years ago

3 0

Kian has to work with 6 square inches

Step-by-step explanation:

Given that the logo has to be created in a rectangular shape

Length = 3 inches

Width = 2 inches

We have to calculate the area of the given space to find out that how much area Kian will work with.

So,

$Area = Length*Width\\=2*3\\=6\ in^2$

Hence,

Kian has to work with 6 square inches

Keywords: Rectangle, Area

Learn more about rectangle at:

#LearnwithBrainly

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White raven [17]

The correct answer would be 42.50

Work:

50 divided by 100 = .5

.5 * 15 = 7.5

50 - 7.5 = 42.50.

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3 years ago

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Answer:

Step-by-step explanation:

Given

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Answer:

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explanation:

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2 years ago

The average daily rainfall for the past week in the town of Hope Cove is normally distributed, with a mean rainfall of 2.1 inche

natita [175]

Answer:

Step-by-step explanation:

We calculate the z-score for each

Mathematically;

z-score = (x-mean)/SD

z1 = (1.9-2.1)/0.2 = -1

z2 = (2.3-2.1)/0.2 = 1

So the proportion we want to calculate is;

P(-1<x<1)

We use the standard score table for this ;

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3 years ago

How does the sample size affect the validity of an empirical argument? A. The larger the sample size the better. B. The smaller

astra-53 [7]

Answer:

A. The larger the sample size the better.

Step-by-step explanation:

Central Limit Theorem

The Central Limit Theorem establishes 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 $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean $\mu = p$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}}$

In this question:

We have to look at the standard error, which is:

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

This means that an increase in the sample size reduces the standard error, and thus, the larger the sample size the better, and the correct answer is given by option a.

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3 years ago