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SOVA2 [1]
2 years ago
6

Ian owns a small business selling used books. He knows that in the last week 122 customers paid cash, 14 customers used a debit

card, and 4 customers used a credit card.
Mathematics
1 answer:
Veronika [31]2 years ago
5 0

The number of customer you expect to pay with a credit card will be 51 customers.

<h3>How to find that a given condition can be modeled by binomial distribution?</h3>

Binomial distributions consist of n independent Bernoulli trials.

The expected value will be

E(X) = np

Ian owns a small business selling used books.

He knows that in the last week 122 customers paid cash, 14 customers used a debit card, and 4 customers used a credit card.

If next week, he is expecting 1800 customers.

Then the number of the customer you expect to pay with a credit card will be

n = 1800

The probability of the customer who pays with a credit card will be

p = 4/140

p = 0.02587

Then the expected value will be

E(x) = 1800 x 0.02587

E(x) = 51.42

E(x) ≅ 51

Learn more about binomial distribution here:

brainly.com/question/13609688

#SPJ1

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We are asked to determine the correlation factor "r" of the given table. To do that we will first label the column for "Quality" as "x" and the column for "Easiness" as "y". Like this:

Now, we create another column with the product of "x" and "y". Like this:

Now, we will add another column with the squares of the values of "x". Like this:

Now, we add another column with the squares of the values of "y":

Now, we sum the values on each of the columns:

Now, to get the correlation factor we use the following formula:

r=\frac{n\Sigma xy-\Sigma x\Sigma y}{\sqrt{(n\Sigma x^2-(\Sigma x)^2)(n\Sigma y^2-(\Sigma y)^2)}}

Where:

\begin{gathered} \Sigma xy=\text{ sum of the column of xy} \\ \Sigma x=\text{ sum of the column x} \\ \Sigma y=\text{ sum of the column y} \\ \Sigma x^2=\text{ sum of the column x\textasciicircum2} \\ \Sigma y^2=\text{ sum of the column y\textasciicircum2} \\ n=\text{ number of rows} \end{gathered}

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r=\frac{\left(6)(70.56)-(25.2)(16.4\right)}{\sqrt{((6)(107.12)-(25.2)^2)((6)(47.82)-(16.4)^2)}}

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r=0.858

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