Which angles are supplementary to eachother

QUESTION 3 - Distinguish whether the following pairs of events are dependent

TiliK225 [7]

Two eventis are independent if knowledge about the first doesn't change your expectation about the second.

a) Independent: After you know that the first die showed 4, you stille expect all 6 numbers from the second. So, the fact that the first die showed 4 doesn't change your expectation about the second die: it can still show numbers from 1 to 6 with probability 1/6 each.

b) Independent: It's just the same as before. After you know that the first coin landed on heads, you still expect the second coin to land on heads or tails with probability 1/2 each. Knowledge about the first coin changed nothing about your expectation about the second coin.

a) Dependent: In this case, there is a cause-effect relation, so the events are dependent: knowing that a person is short-sighted makes you almost sure that he/she will wear glasses. So, knowledge about being short sighted changed your expectation about wearing glasses.

8 0

4 years ago

Find the probability that a randomly

vazorg [7]

Answer:

Step-by-step explanation:

3 0

3 years ago

According to the National Vital Statistics, full-term babies' birth weights are Normally distributed with a mean of 7.5 pounds a

Sav [38]

Answer:

68.26% probability that a randomly selected full-term pregnancy baby's birth weight is between 6.4 and 8.6 pounds

Step-by-step explanation:

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.

In this problem, we have that:

$\mu = 7.5, \sigma = 1.1$

What is the probability that a randomly selected full-term pregnancy baby's birth weight is between 6.4 and 8.6 pounds

This is the pvalue of Z when X = 8.6 subtracted by the pvalue of Z when X = 6.4. So

X = 8.6

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

$Z = \frac{8.6 - 7.5}{1.1}$

$Z = 1$

$Z = 1$ has a pvalue of 0.8413

X = 6.4

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

$Z = \frac{6.4 - 7.5}{1.1}$

$Z = -1$

$Z = -1$ has a pvalue of 0.1587

0.8413 - 0.1587 = 0.6826

68.26% probability that a randomly selected full-term pregnancy baby's birth weight is between 6.4 and 8.6 pounds

6 0

3 years ago

1+2+3+4+5+6.......+99 what is the quickest way to find the answer Thank u

serious [3.7K]

Answer:

Step-by-step explanation:

Use the formula Sum = (a + L)*n/2

The tricky part is n. That's the number of terms between 1 and 99 inclusive.

n = 99 -1 + 1 = 99

n = 99

a = 1

L = 99

Sum = (1 + 99)*99 / 2

Sum = (100)*99/2

Sum = 4950

3 0

3 years ago

Read 2 more answers

Pls help i need this done as quick as possible

Anvisha [2.4K]

Answer:

Infinite Solutions.

Step-by-step explanation:

$m+7=3+m+4$

Subtract m from both sides:

$m+7-m=3+m+4-m$

$7=3+4$

$7=7$

Both sides are equal.

This means that the value of m does not affect the end result of 7 = 7, which is true. Thus, there are infinite solutions as any value of m will still make the equation true.

4 0

3 years ago