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Valentin [98]
3 years ago
6

To French shop for fresh fruit. Elena buys a watermelon for $7.75 and 5 pounds of cherries Tammy buys a pineapple for $4.15 and

4 pounds of cherries. Use the variable peer to represent the price in dollars per pound of cherries. Right and simplify and expression to represent how much more Alina spent
Mathematics
1 answer:
lys-0071 [83]3 years ago
8 0

Answer: Elena spent $3.6 +x more than Tammy.

Step-by-step explanation:

Let the cost of each cherry be 'x'.

Cost of watermelon for Elena = $7.75

Cost of 5 pounds of cherries = 5x

So, Equation for Elena would be

7.75+5x

Cost of pineapple = $4.15

Number of pounds of cherries = 4

So, Equation for Tammy would be

\$4.15+4x

Now, Elena spent more than Tammy by

(7.75+5x)-(4.15+4x)\\\\=7.75+5x-4.15-4x\\\\=3.6+x

Hence, Elena spent $3.6 +x more than Tammy.

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Step-by-step explanation:

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Find gradient and y-intercept of<br>Y=3x-5​
NemiM [27]

Answer:

Slope <em>m</em> (Gradient) = 3

y-intercept: (0, -5)

General Formulas and Concepts:

<u>Algebra I</u>

Slope-Intercept Form: y = mx + b

  • m - slope
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<u>Step 1: Define</u>

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Slope <em>m</em> = 3

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Read 2 more answers
The process standard deviation is 0.27, and the process control is set at plus or minus one standard deviation. Units with weigh
mr_godi [17]

Answer:

a) P(X

And for the other case:

tex] P(X>10.15)[/tex]

P(X>10.15)= P(Z > \frac{10.15-10}{0.15}) = P(Z>1)=1-P(Z

So then the probability of being defective P(D) is given by:

P(D) = 0.159+0.159 = 0.318

And the expected number of defective in a sample of 1000 units are:

X= 0.318*1000= 318

b) P(X

And for the other case:

tex] P(X>10.15)[/tex]

P(X>10.15)= P(Z > \frac{10.15-10}{0.05}) = P(Z>3)=1-P(Z

So then the probability of being defective P(D) is given by:

P(D) = 0.00135+0.00135 = 0.0027

And the expected number of defective in a sample of 1000 units are:

X= 0.0027*1000= 2.7

c) For this case the advantage is that we have less items that will be classified as defective

Step-by-step explanation:

Assuming this complete question: "Motorola used the normal distribution to determine the probability of defects and the number  of defects expected in a production process. Assume a production process produces  items with a mean weight of 10 ounces. Calculate the probability of a defect and the expected  number of defects for a 1000-unit production run in the following situation.

Part a

The process standard deviation is .15, and the process control is set at plus or minus  one standard deviation. Units with weights less than 9.85 or greater than 10.15 ounces  will be classified as defects."

Previous concepts

Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".

The Z-score is "a numerical measurement used in statistics of a value's relationship to the mean (average) of a group of values, measured in terms of standard deviations from the mean".  

Solution to the problem

Let X the random variable that represent the weights of a population, and for this case we know the distribution for X is given by:

X \sim N(10,0.15)  

Where \mu=10 and \sigma=0.15

We can calculate the probability of being defective like this:

P(X

And we can use the z score formula given by:

z=\frac{x-\mu}{\sigma}

And if we replace we got:

P(X

And for the other case:

tex] P(X>10.15)[/tex]

P(X>10.15)= P(Z > \frac{10.15-10}{0.15}) = P(Z>1)=1-P(Z

So then the probability of being defective P(D) is given by:

P(D) = 0.159+0.159 = 0.318

And the expected number of defective in a sample of 1000 units are:

X= 0.318*1000= 318

Part b

Through process design improvements, the process standard deviation can be reduced to .05. Assume the process control remains the same, with weights less than 9.85 or  greater than 10.15 ounces being classified as defects.

P(X

And for the other case:

tex] P(X>10.15)[/tex]

P(X>10.15)= P(Z > \frac{10.15-10}{0.05}) = P(Z>3)=1-P(Z

So then the probability of being defective P(D) is given by:

P(D) = 0.00135+0.00135 = 0.0027

And the expected number of defective in a sample of 1000 units are:

X= 0.0027*1000= 2.7

Part c What is the advantage of reducing process variation, thereby causing process control  limits to be at a greater number of standard deviations from the mean?

For this case the advantage is that we have less items that will be classified as defective

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Calculate the amount and the compound interest on Rs 12.000 in 2 years at 10%
mel-nik [20]

Answer:

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Compund interest = amount - principal

= 14520 - 12000

= 2520rs.

Next question :- no of men can complete a piece of work in 7 days = 36

No of men can complete a piece of work in 42 day = ( 36 x 7 ) ÷ 42

= 252 ÷ 42

= 6 men

5 0
2 years ago
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