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dezoksy [38]
3 years ago
10

It takes the hot water faucet 4 times as long to fill a bathtub as it does the cold water faucet. Left on together, the cold and

hot water faucets take 3 minutes to fill the tub. How long will it take the cold water faucet to fill the tub by itself
Mathematics
1 answer:
Debora [2.8K]3 years ago
3 0

If it takes the cold water faucet x minutes to fill 1 tub, then its flow rate is (1 tub)/(x min).

The hot water faucet takes 4 times as long, so its flow rate is (1 tub)/(4x min).

Together, the total flow rate is (1 tub)/(3 min), so we have

\dfrac1x+\dfrac1{4x}=\dfrac13

\implies\dfrac5{4x}=\dfrac13

\implies15=4x

\implies x=\dfrac{15}4\,\text{min}=3\,\text{min}\,45\,\text{sec}

You might be interested in
Convert 4875m to metres​
Digiron [165]
4875m is miles so 7845552 meters
8 0
3 years ago
A civil engineer is analyzing the compressive strength of concrete. Compressive strength is normally distributed with A random s
wel

Answer:

95%: (3278.354 ; 3270.083)

99% : (3221.646 ; 3278.354)

Step-by-step explanation:

Given :

Sample size, n = 12

Mean, xbar = 3250

Sample standard deviation = √1000

The 95% confidence interval :

Mean ± Margin of error

Margin of Error = Tcritical * s/√n

Tcritical at 0.05, df=12-1 = 11 ;

Tcritical at 95% = 2.20

Hence,

Margin of Error = (2.20 * √1000/√12) = 20.083

Confidence interval : 3250 ± 20.083

Lower boundary = 3250 - 20.083 = 3229.917

Upper boundary = 3250 + 20.083 = 3270.083

2.)

The 99% confidence interval :

Mean ± Margin of error

Margin of Error = Tcritical * s/√n

Tcritical at 0.01, df=12-1 = 11 ;

Tcritical at 99% = 3.106

Hence,

Margin of Error = (3.106 * √1000/√12) = 28.354

Confidence interval : 3250 ± 28.354

Lower boundary = 3250 - 28.354 = 3221.646

Upper boundary = 3250 + 28.354 = 3278.354

3 0
3 years ago
Help me please im so mad :(:
Len [333]

Answer:

R- (-10, -3)

S- (-10, -6)

Q- (-5, -3)

P- (-5, -6)

Step-by-step explanation:

Well, Q and P would be the exact same coordinates since that land directly on the reflection line.

Basically, on this graph/question you can count how far away the vertices is from the reflection line.

For example, Point R is 5 units away from the reflection line, therefore I need to count over 5 times to the left from the reflection line for point R. (Idk if that makes sense or not, ask questions if you are confused).

5 0
3 years ago
Read 2 more answers
I camper attaches a rope from the top of her tent 4 feet above the ground to give it more support if the Rope is 8 ft long about
iVinArrow [24]

Answer:

b = 6.928

Step-by-step explanation:

Looks like a job for the Pythagorean Theorem.

a^2 + b^2 = c^2

4^2 + b^2 = 8^2

16 + b^2 = 64

b^2 = 48

b = 6.928

Hope it helps!!

6 0
3 years ago
. In a study of air-bag effectiveness it was found that in 821 crashes of midsize cars equipped with air bags, 46 of the crashes
jok3333 [9.3K]

Answer:

P(X ≤ 46 | X~B(821, 0.078)) = 0.00885745584

0.00885... < 0.01

The test statistic of 46 is significant

There is sufficient evidence to reject H₀ and accept H₁

Air bags are more effective as protection than safety belts

Step-by-step explanation:

821 crashes

46 hospitalisations where car has air bags

7.8% or 0.078 probability of hospitalisations in cars with automatic safety belts

α = 0.01 or 1% ← level of significance

One-tailed test

We are testing whether hospitalisations in cars with air bags are less likely than in a car with automatic safety belts;

The likelihood of hospitalisation in a car with automatic safety belts, we are told, is 7.8% or 0.078;

So we are testing if hospitalisations in cars with air bags is less than 0.078;

So, firstly:

Let X be the continuous random variable, the number of hospitalisations from a car crash with equipped air bags

X~B(821, 0.078)

Null hypothesis (H₀): p = 0.078

Alternative hypothesis (H₁): p < 0.078

According to the information, we reject H₀ if:

P(X ≤ 46 | X~B(821, 0.078)) < 0.01

To find P(X ≤ 46) or equally P(X < 47), it could be quite long-winded to do manually for this particular scenario;

If you are interested, the manual process involves using the formula for every value of x up to and including 46, i.e. x = 0, x = 1, x = 2, etc. until x = 46, the formula is:

P(X = r) = nCr * p^{r}  * (1 - p)^{n - r}

You can find binomial distribution calculators online, where you input n (i.e. the number of trials or 821 in this case), probability (i.e. 0.078) and the test statistic (i.e. 46), it does it all for you, which gives:

P(X ≤ 46 | X~B(821, 0.078)) = 0.00885745584

Now, we need to consider if the condition for rejecting H₀ is met and recognise that:

0.00885... < 0.01

There is sufficient evidence to reject H₀ and accept H₁.

To explain what this means:

The test statistic of 46 is significant according to the 1% significance level, meaning the likelihood that only 46 hospitalisations are seen in car crashes with air bags in the car as compared to the expected number in car crashes with automatic safety belts is very unlikely, less than 1%, to be simply down to chance;

In other words, there is 99%+ probability that the lower number of hospitalisations in car crashes with air bags is due to some reason, such as air bags being more effective as a protective implement than the safety belts in car crashes.

5 0
2 years ago
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