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Alex777 [14]
1 year ago
5

Suppose you like to keep a jar of change on your desk currently at the jar contains the followingWhat is the probability that yo

u reach into the jar and grab a penny and then without replacement a dime? Express your answer as a fraction or decimal number rounded to four decimal places

Mathematics
1 answer:
Tju [1.3M]1 year ago
7 0
Answer:

The probability of a penny and then without replacement a dime = 7/376

Explanation:

Given:

A jar contains:

6 Pennies, 7 Dimes, 16 Nickels, and 19 Quarters

To find:

the probability when you reach into the jar and grab a penny and then without replacement a dime

Total coins = 6 + 7 + 16 + 19

Total coins = 48

Probability of picking a penny = number of pennies/total coins

Probability of picking a penny = 6/48

Probability of picking a dime after a penny without replacement:

Since we are not replacing the first pick, the total coins will reduce by 1

Total coin for 2nd pick = 48 - 1 = 47

Pr(dime after a penny without replacement) = number of dime/total coin

Pr(dime after a penny without replacement) = 7/47

The probability of a penny and then without replacement a dime = Probability of picking a penny ×

Pr(dime after a penny without replacement)

\begin{gathered} Pr(penny,\text{ then a dime without replacement\rparen= }\frac{6}{48}\times\frac{7}{47} \\  \\ Pr(penny,\text{ then a dime without replacement\rparen= }\frac{1}{8}\times\frac{7}{47} \\  \\ Pr(penny,\text{ then a dime without replacement\rparen= }\frac{7}{376\frac{}{}} \\  \\ Pr(penny,\text{ then a dime without replacement\rparen= 0.0186} \end{gathered}

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What is 1×1,000+3×10,000+9×1,000+8×100+5×10+2×1
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Use PEMDAS for this problem.
1 x 1000=   + 1000
3 x 10,000= 30,000
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Hoped this helped.

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6 0
3 years ago
Suppose the following number of defects has been found in successive samples of size 100: 6, 7, 3, 9, 6, 9, 4, 14, 3, 5, 6, 9, 6
Brut [27]

Answer:

Given the data in the question;

Samples of size 100: 6, 7, 3, 9, 6, 9, 4, 14, 3, 5, 6, 9, 6, 10, 9, 2, 8, 4, 8, 10, 10, 8, 7, 7, 7, 6, 14, 18, 13, 6.

a)

For a p chart ( control chart for fraction nonconforming), the center line and upper and lower control limits are;

UCL = p" + 3√[ (p"(1-P")) / n ]

CL = p"

LCL = p" - 3√[ (p"(1-P")) / n ]

here, p" is the average fraction defective

Now, with the 30 samples of size 100

p" =  [∑(6, 7, 3, 9, 6, 9, 4, 14, 3, 5, 6, 9, 6, 10, 9, 2, 8, 4, 8, 10, 10, 8, 7, 7, 7, 6, 14, 18, 13, 6.)] / [ 30 × 100 ]

p" = 234 / 3000

p" = 0.078

so the trial control limits for the fraction-defective control chart are;

UCL = p" + 3√[ (p"(1-P")) / n ]

UCL = 0.078 + 3√[ (0.078(1-0.078)) / 100 ]

UCL = 0.078 + ( 3 × 0.026817 )

UCL = 0.078 + 0.080451

UCL = 0.1585

LCL = p" - 3√[ (p"(1-P")) / n ]

LCL = 0.078 - 3√[ (0.078(1-0.078)) / 100 ]

LCL = 0.078 - ( 3 × 0.026817 )

LCL = 0.078 - 0.080451

LCL =  0 ( SET TO ZERO )

Diagram of the Chart uploaded below

b)

from the p chart for a) below, sample 28 violated the first western electric rule,

summary report from Minitab;

TEST 1. One point more than 3.00 standard deviations from the center line.

Test failed at points: 28

Hence, we conclude that the process is out of statistical control

Lets Assume that assignable causes can be found to eliminate out of control points.

Since 28 is out of control, we should eliminate this sample and recalculate the trial control limits for the P chart.

so

p" = 0.0745

UCL = p" + 3√[ (p"(1-P")) / n ]

UCL = 0.0745 + 3√[ (0.0745(1-0.0745)) / 100 ]

UCL = 0.0745 + ( 3 × 0.026258 )

UCL = 0.0745 + 0.078774

UCL = 0.1532

LCL  = p" - 3√[ (p"(1-P")) / n ]

LCL = 0.0745 - 3√[ (0.0745(1-0.0745)) / 100 ]

LCL = 0.0745 - ( 3 × 0.026258 )

LCL = 0.0745 - 0.078774

UCL = 0  ( SET TO ZERO )

The second p chart diagram is upload below;

NOTE; the red circle symbol on 28 denotes that the point is not used in computing the control limits

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