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A coffee shop collected the following information regarding purchases from 110 of its customers 59 purchased coffee 39 purchased

Andrej [43]

Answer:

Let X be the number of customer purchased coffee

Let Y be the number of customer purchased donuts

Then $X\cap Y$ is the number of customer purchased both coffee and donuts

$X\cup Y$ is the number of customer purchased both coffee or donuts

The Number of customers purchased only Coffee:

Number of customers purchased only donuts =n(X -Y)

$n( X -Y) = n(X) - n(X \cap Y)$

n(X-Y) = 59 -16

n(Y - X) = 43

The Number of customers purchased only donuts:

Number of customers purchased only donuts =n(Y -X)

$n(Y - X) = n(Y) - n(X \cap Y)$

n(Y - X) = 39 -16

n(Y - X) = 23

The Number of customers did not purchase either of these items:

Number of customers did not purchase either of these items = $n(X\cup Y)^{\prime}$

First lets find $n(X\cup Y)$

$n(X\cup Y) = n(X) + n(Y) - n( X \cap Y)$

$n(X\cup Y) = 59 + 39 - 16$

$n(X\cup Y) = 82$

$n(X\cup Y)^{\prime}$ = $110 - n(X\cup Y)$ = 28

5 0

4 years ago

The triangles are congruent by SSS or HL. Triangles M N Q and P Q N are connected at side Q N. Triangle M N Q is rotated about p

forsale [732]

Answer:the last one

Step-by-step explanation:

6 0

3 years ago

Read 2 more answers

You are collecting a sample of 60 data points from a population that you know to follow an exponential distribution. It is not a

11111nata11111 [884]

Answer:

For the exponential distribution:

$\mu = \frac{1}{\lambda}$

$\sigma^2 = \frac{1}{\lambda^2}$

We know that the exponential distribution is skewed but the sample mean for this case using a sample size of 60 would be approximately normal, so then we can conclude that if we have a sample size like this one and an exponential distribution we can approximate the sample mean to the noemal distribution and indeed use the Central Limit theorem.

$\bar X \sim N(\mu_{\bar X} , \frac{\sigma}{\sqrt{n}})$

$\mu_{\bar X} = \bar X$

$\sigma_{\bar X}= \frac{\sigma}{\sqrt{n}}$

Step-by-step explanation:

The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".

For this case we have a large sample size n =60 >30

The exponential distribution is the probability distribution that describes the time between events in a Poisson process.

For the exponential distribution:

$\mu = \frac{1}{\lambda}$

$\sigma^2 = \frac{1}{\lambda^2}$

We know that the exponential distribution is skewed but the sample mean for this case using a sample size of 60 would be approximately normal, so then we can conclude that if we have a sample size like this one and an exponential distribution we can approximate the sample mean to the noemal distribution and indeed use the Central Limit theorem.

$\bar X \sim N(\mu_{\bar X} , \frac{\sigma}{\sqrt{n}})$

$\mu_{\bar X} = \bar X$

$\sigma_{\bar X}= \frac{\sigma}{\sqrt{n}}$

5 0

4 years ago

Calculate the lateral surface area of the rectangular prism:

bekas [8.4K]

Find the area of all six rectangular faces of the prism. (A= l x b)

A1: 3.1 x 5 = 15.5
A2: 7.4 x 3.1 = 22.94
A3: 5 x 7.4 = 37
A4: 3.1 x 7.4 = 22.94
A5: 7.4 x 5 = 37
A6: 3.1 x 5 = 15.5

Add all answers together to get your answer of 150.88 cm^2.
Hope this helps!!

8 0

3 years ago

What are two numbers that add up to 5 and multiply to -24

Ganezh [65]

Answer:

-4 and 6

Step-by-step explanation:

6 0

3 years ago

Read 2 more answers