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weeeeeb [17]
3 years ago
6

WILL GIVE BRAINLIST MATH

Mathematics
1 answer:
Artyom0805 [142]3 years ago
3 0
It’s basically asking you to put it into the graph. Least to greatest.
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Wren bought a baseball card last year for $2.25. This year the price dropped to $.45. What was the percent of decrease in the pr
const2013 [10]
The price:
- last year: $2.25
- this year: $.45
The decrease: $2.25 - $.45 = $1.80
2.25 : 1.80 = 100 : x
2.25 x = 180
x = 180 : 2.25
x = 80
Answer:
The percent of decrease is  A ) 80%
4 0
3 years ago
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

5 0
3 years ago
A 6-sided die with sides numbered 1 through 6 is tossed. A penny is then tossed. If the penny comes up heads, the value of the d
Montano1993 [528]

Answer:

The probability that the outcome is less than 6 is 58.333%.

Step-by-step explanation:

Since a 6-sided die with sides numbered 1 through 6 is tossed, ya penny is then tossed, and if the penny comes up heads, the value of the die is multiplied by 2, but otherwise, the value of the die is left unchanged, to determine what is the probability that the outcome is less than 6 the following calculation must be performed:

(5/6 + 2/6) / 2 = X

(0.8333 + 0.0333) / 2 = X

1.1666666 / 2 = X

0.583333 = X

Therefore, the probability that the outcome is less than 6 is 58.333%.

5 0
2 years ago
A runner starts from rest and accelerates uniformly to a speed of 8.0 meters per
ivanzaharov [21]

2 m/s²

Step-by-step explanation:

Step 1:

Let the initial velocity be 0 m/s and the final velocity be 8 m/s and the time traveled is 4 s.

From the basic science,

Acceleration = ( Final Velocity - Initial Velocity) / Time

Step 2:

Acceleration = (8-0)/4

2 m/s²

4 0
3 years ago
Please help me thanks
elena-s [515]

Answer: need more info dude



3 0
3 years ago
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