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3 years ago

How many minutes are there from 01:33hr to 03:18hr on the same day

Mathematics

2 answers:

Flura [38]3 years ago

5 0

Answer: 105 minute’s

Step-by-step explanation:

1:33+27= 2:00

2:00+ 78 (1 hour 18 minutes) = 3:18

78+27=105

goldfiish [28.3K]3 years ago

3 0

3:18-1:33=188 so I think that’s ur answer

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What is the area of a 45 degree sector of a circle with a radius of 12 in.

Elodia [21]

given ,

a circle of radius 12 inches

and $\theta$ = 45°

now we know that ,

$\\{Area \: of \: sector = \frac{\theta}{360\degree} \times \pi \: r {}^{2} } \\ \\$

let's now plug in the values of radius and theta as 12 inches and 45° respectively ,

$\\\dashrightarrow \: \frac{45}{360} \times \frac{22}{7} \times 12 \times 12 \\ \\ \dashrightarrow \: \frac{1}{8} \times \frac{22 \times 12 \times 12}{7} \\ \\ \dashrightarrow \: \frac{22 \times 12 \times 12}{56} \\ \\ \dashrightarrow \: \frac{3168}{56} \\ \\ \dashrightarrow \: 56.57 \: inches {}^{2} (approx.)$

hope helpful :D

6 0

3 years ago

Solve -5w = -80 for w.<br><br> w =

Aleks [24]

Answer:

w=4

Step-by-step explanation:

-80/-5=4

6 0

3 years ago

Read 2 more answers

A population has a mean of 200 and a standard deviation of 50. Suppose a sample of size 100 is selected and x is used to estimat

zmey [24]

Answer:

a) 0.6426 = 64.26% probability that the sample mean will be within +/- 5 of the population mean.

b) 0.9544 = 95.44% probability that the sample mean will be within +/- 10 of the population mean.

Step-by-step explanation:

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

Normal probability distribution

When the distribution is normal, we use 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 normally distributed random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$ .