All categories

2 years ago

In circle Y, what is m∠1?6°25°31°37°

Mathematics

2 answers:

elixir [45]2 years ago

7 0

Answer:

Step-by-step explanation:

dont listen to the other dude

marissa [1.9K]2 years ago

3 0

Answer:

Step-by-step explanation:

You might be interested in

Y is 5 less than the square of the sum of p and q.

guajiro [1.7K]

Answer:

y = (p+q)² - 5

Step-by-step explanation:

Use the wording to do this:

y = (p+q)² - 5

3 0

3 years ago

the perimeter of the floor of a room is 18 metre and its height is 3 cm what is the area of 4 walls of the room

Lina20 [59]

Note: The height of the room must be 3 m instead of 3 cm because 3 cm is too small and it cannot be the height of a room.

Given:

Perimeter of the floor of a room = 18 metre

Height of the room = 3 metre

To find:

The area of 4 walls of the room.

Solution:

We know that, the area of 4 walls of the room is the curved surface area of the cuboid room.

The curved surface area of the cuboid is

$C.S.A.=2h(l+b)$

Where, h is height, l is length and b is breadth.

Perimeter of the rectangular base is 2(l+b). So,

$C.S.A.=\text{Perimeter of the base} \times h$

Putting the given values, we get

$C.S.A.=18\times 3$

$C.S.A.=54$

Therefore, the area of 4 walls of the room is 54 sq. metres.

7 0

3 years ago

In college basketball, a shot made from beyond a designated arc radiating about 20 ft from the basket is worth three points ins

denis-greek [22]

Answer:

a) By the Central Limit Theorem, the distribution would be approximately normal, with mean $\mu = 0.45$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.45*0.55}{100}} = 0.0497$

b) 4.02 standard deviations below the mean.

c) Making 25 or less shots has a pvalue of -4.02. Z-scores lower than -2 are considered surprising, so yes, it would be surprising for him to make only 25 of these shots.

Step-by-step explanation:

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

Normal probability distribution

Problems of normally distributed samples are 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 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 $s = \frac{\sigma}{\sqrt{n}}$ .

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

For proportions, we have that the mean is $\mu = p$ and the standard deviation is $s = \sqrt{\frac{p(1-p)}{n}}$

In this problem, we have that:

$p = 0.45, n = 100$

a)By the Central Limit Theorem, the distribution would be approximately normal, with mean $\mu = 0.45$ and standard deviation $s = \sqrt{\frac{p(1-p)}{n}} = \sqrt{\frac{0.45*0.55}{100}} = 0.0497$

b)This is Z when X = 0.25.

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

By the Central Limit Theorem

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