The graph below shows the solutions to which inequality?

During the national day celebrations.Asha decorates her balcony with serial lights of red,green and white colours.The red light

expeople1 [14]

If all three coloured lights blink together at 8:49 pm, they will blink together at 8:50 pm

Solution:

Given that the red light blinks at intervals of 4 seconds, the green at 5 seconds and the white at 6 seconds.

If all three colored lights blink together at 8:49 pm,

We have to find when will they blink together again?

First let us know, at what intervals they all together blink.

For that we have to find the lcm of 4, 5, 6.

L.C.M (4, 5, 6) = 2 x L.C.M(2, 5, 3)

As 2,3,5 are primes, we can’t take common further, so multiply all

= 2 x 2 x 5 x 3

= 4 x 15 = 60

So, after every 60 seconds = 1 minute they will blink.

Then, after 8 : 49 pm, they will blink at 8 : 49 + 1 = 8 : 50 pm.

Hence, they all blink at 8 : 50 pm.

6 0

3 years ago

The smallest number that is divisible by 2, 3, 4, 5, 6, 8, and 10 is...

Ratling [72]

I don't think a number like that exists :/

5 0

3 years ago

Please help, would be greatful

olchik [2.2K]

Answer:

h = 7.7 cm

Step-by-step explanation:

you can create a proportion using Law of Sines

sin 90 = sin 31

15 h

1 = 0.515

15 h

h ≈ 7.7

8 0

3 years ago

The body temperatures of adults are normally distributed with a mean of 98.6degrees° F and a standard deviation of 0.60degrees°

Schach [20]

Answer:

97.72% probability that their mean body temperature is greater than 98.4degrees° F.

Step-by-step explanation:

To solve this question, we have to understand the normal probability distribution and the central limit theorem.

Normal probability distribution:

Problems of normally distributed samples can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the zscore of a measure X is given by:

$Z = \frac{X - \mu}{\sigma}$

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

Central limit theorem:

The Central Limit Theorem estabilishes that, for a random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sample means with size n of at least 30 can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$