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Rainbow [258]
2 years ago
11

Please help. I need to finish this before 10:20

Mathematics
1 answer:
goldenfox [79]2 years ago
6 0

The probability that a customer ordered a large given that he or she ordered a cold drink is 20%

<h3>How to determine the probability?</h3>

The probability is represented as:

P(Ordered large | Cold drink)

It is calculated using:

P(Ordered large | Cold drink) = n(Ordered large and Cold drink) / n(Cold drink)

Using the values in the table, we have:

P(Ordered large | Cold drink) = 5/(8 + 12 + 5)

Evaluate

P(Ordered large | Cold drink) = 0.2

Express as percentage

P(Ordered large | Cold drink) = 20%

Hence, the probability that a customer ordered a large given that he or she ordered a cold drink is 20%

Read more about probability at:

brainly.com/question/25870256

#SPJ1

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An auto manufacturing company wanted to investigate how the price of one of its car models depreciates with age. The research de
sertanlavr [38]

Answer:

a)

Price=150.414-16.626 Age

b)

$34.032

c)

We can't estimate the price of 18 year old car using the above regression equation because the price of 18 year old car falls outside the scope of the model

Step-by-step explanation:

Age(X)   Price(Y)

8              18

3              94

6              50

9              21

2              145

5              42

6              36

3              99

a)

The regression equation can be written as

y=a+bx

b=\frac{sum(x-xbar)(y-ybar)}{sum(x-xbar)^{2} }

a=ybar-bxbar

xbar=sumx/n

xbar=(8+3+6+9+2+5+6+3)/8=5.25

ybar=sumy/n

ybar=(18+94+50+21+145+42+36+99)/8=63.125

x y x-xbar y-ybar (x-xbar)^2 (x-xbar)(y-ybar)

8 18 2.75  -45.125 7.5625        -124.09375

3 94 -2.25 30.875 5.0625        -69.46875

6 50 0.75 -13.125 0.5625        -9.84375

9 21 3.75  -42.125 14.0625        -157.96875

2 145 -3.25 81.875 10.5625        -266.09375

5 42 -0.25 -21.125 0.0625         5.28125

6 36 0.75 -27.125 0.5625        -20.34375

3 99 -2.25 35.875 5.0625        -80.71875

Total             43.5        -723.25

b=\frac{sum(x-xbar)(y-ybar)}{sum(x-xbar)^{2} }

b=-723.25/43.5

b=-16.626

a=ybar-bxbar

a=63.125-(16.626)*5.25

a=150.414

Thus, the required regression equation is

y=150.414-16.626 x

Price=150.414-16.626 Age

b)

For predicting price of 7 years old car we put x=7 in the estimated regression equation

y=150.414-16.626 x

y=150.414-16.626(7)

y=150.414-116.382

y=34.032

The predicted price of a 7 year old car is $34.032.

c)

We can't estimate the price of 18 year old car using the above regression equation because the price of 18 year old car falls outside the scope of the model. The estimate of price is only valid for 2 to 9 year old car.

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