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nadezda [96]
3 years ago
14

A grocery store chain has been tracking data on the number of shoppers that use coupons. The data shows that 71% of all shoppers

use coupons. 18 times out of 20 these results were considered accurate to within 2.5%
Mathematics
2 answers:
sesenic [268]3 years ago
6 0

<span>The computation for the confidence level = (18/20) x 100% = 90 %, the E or the margin error = 0.023 and the p = to 0.71. Confidence interval can be achieved by using the formula (p-E, p+E) = (0.71-0.025, 0.71+0.025). Therefore, the confidence interval is (0.685,0.735).</span>

Y_Kistochka [10]3 years ago
3 0

Answer:

90%

Step-by-step explanation:

18/20 = .9

.9*100= 90%

You might be interested in
Use rounding to estimate the product.8 × 9.82
aleksley [76]

Answer:

8 * 9.82 ≈ 8 * 10 = 80

Step-by-step explanation:

9.82 ≈ 10

8 * 10 = 80

4 0
2 years ago
The number of yards of fabric needed for Robs costume is (7/8+1/2+1 3/4)÷2. How does the amount of fabric needed for Robs costum
exis [7]

The amount of fabric needed for Jimmy's costume is not stated, we can only determine the amount needed for Rob's costume, which makes it impossible to compare the amounts needed for both of their costumes. If this omission was an error, then you can find the difference between these amounts if the amount needed for Jimmy's costume is stated explicitly.

Step-by-step explanation:

The number of yards of fabric needed for Robs costume is (7/8+1/2+1 3/4)÷2

Assuming 1 3/4 is a mixed fraction.

= (7/8 + 1/2 + 7/4) ÷ 2

= (7 + 4 + 2) ÷ (8 × 2)

= 13/16 yards

Suppose 2 yards of fabric is needed for Jimmy's costume, then comparing with Rob's yards, we see that Jimmy's costume requires (2 - 13/16 = 19/16) more yards than Rob's costume.

8 0
3 years ago
Simplify this expression
antiseptic1488 [7]

Answer:

2/(3x-2)²

Step-by-step explanation:

4x²-6x³-2x²+6x³/4x²-6x³-6x³+9x^4=

2x²/4x²-12x³+9x^4=

2x²/x²(4-12x+9x²)=

2/9x²-12x+4

2/(3x-2)²

6 0
3 years ago
What is m∠PTR? a. 12 b. 40 c. 50 d. 140 HELP!!!
kramer

Answer:

m<PTR = 140°

Step-by-step explanation:

First, find the value of x. To find the value of x, derive an equation which you'd use in solving for x.

m<PTQ = (x + 28)°

m<RTS = (2x + 16)°

m<PTQ = m<RTS (vertical opposite angles are congruent)

Therefore:

x + 28 = 2x + 16

Solve for x. Combine like terms

28 - 16 = 2x - x

12 = x

x = 12

Find m<PTQ

m<PTQ = (x + 28)

plug in the value of x

m<PTQ = 12 + 28 = 40°

m<PTR + m<PTQ = 180° (supplementary angles)

m<PTR + 40° = 180° (substitution)

m<PTR = 180 - 40 (subtracting 40 from each side)

m<PTR = 140°

3 0
2 years ago
United Airlines' flights from Denver to Seattle are on time 50 % of the time. Suppose 9 flights are randomly selected, and the n
Ivanshal [37]

Answer:

<u><em>a) The probability that exactly 4 flights are on time is equal to 0.0313</em></u>

<u><em></em></u>

<u><em>b) The probability that at most 3 flights are on time is equal to 0.0293</em></u>

<u><em></em></u>

<u><em>c) The probability that at least 8 flights are on time is equal to 0.00586</em></u>

Step-by-step explanation:

The question posted is incomplete. This is the complete question:

<em>United Airlines' flights from Denver to Seattle are on time 50 % of the time. Suppose 9 flights are randomly selected, and the number on-time flights is recorded. Round answers to 3 significant figures. </em>

<em>a) The probability that exactly 4 flights are on time is = </em>

<em>b) The probability that at most 3 flights are on time is = </em>

<em>c)The probability that at least 8 flights are on time is =</em>

<h2>Solution to the problem</h2>

<u><em>a) Probability that exactly 4 flights are on time</em></u>

Since there are two possible outcomes, being on time or not being on time, whose probabilities do not change, this is a binomial experiment.

The probability of success (being on time) is p = 0.5.

The probability of fail (note being on time) is q = 1 -p = 1 - 0.5 = 0.5.

You need to find the probability of exactly 4 success on 9 trials: X = 4, n = 9.

The general equation to find the probability of x success in n trials is:

           P(X=x)=_nC_x\cdot p^x\cdot (1-p)^{(n-x)}

Where _nC_x is the number of different combinations of x success in n trials.

            _nC_x=\frac{x!}{n!(n-x)!}

Hence,

            P(X=4)=_9C_4\cdot (0.5)^4\cdot (0.5)^{5}

                                _9C_4=\frac{4!}{9!(9-4)!}=126

            P(X=4)=126\cdot (0.5)^4\cdot (0.5)^{5}=0.03125

<em><u>b) Probability that at most 3 flights are on time</u></em>

The probability that at most 3 flights are on time is equal to the probabiity that exactly 0 or exactly 1 or exactly 2 or exactly 3 are on time:

         P(X\leq 3)=P(X=0)+P(X=1)+P(X=2)+P(X=3)

P(X=0)=(0.5)^9=0.00195313 . . . (the probability that all are not on time)

P(X=1)=_9C_1(0.5)^1(0.5)^8=9(0.5)^1(0.5)^8=0.00390625

P(X=2)=_9C_2(0.5)^2(0.5)^7=36(0.5)^2(0.5)^7=0.0078125

P(X=3)= _9C_3(0.5)^3(0.5)^6=84(0.5)^3(0.5)^6=0.015625

P(X\leq 3)=0.00195313+0.00390625+0.0078125+0.015625=0.02929688\\\\  P(X\leq 3) \approx 0.0293

<em><u>c) Probability that at least 8 flights are on time </u></em>

That at least 8 flights are on time is the same that at most 1 is not on time.

That is, 1 or 0 flights are not on time.

Then, it is easier to change the successful event to not being on time, so I will change the name of the variable to Y.

          P(Y=0)=_0C_9(0.5)^0(0.5)^9=0.00195313\\ \\ P(Y=1)=_1C_9(0.5)^1(0.5)^8=0.0039065\\ \\ P(Y=0)+P(Y=1)=0.00585938\approx 0.00586

6 0
3 years ago
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