Given AQRS-AXYZ, what is the value of tan(Q)?<br><br> A) 3/5<br> B) 3/4<br> C) 4/5<br> D) 4/3

Physics students were modeling the height of a ball once it was dropped from the top of a 10 foot ladder. The

julsineya [31]

Answer:

<em>Interval notation: [0, 2.236]</em>

<em>Set Builder notation: </em> $\{t\ |\ 0\le t\le 2.236\}$

Step-by-step explanation:

Given that:

Equation of height of the ball dropped from a height of 10 foot, as:

$h(t) = 10 - 2t^2$

Where $t$ is the time since the ball was dropped.

To find:

The domain of the function in Interval and set builder notation.

Solution:

<em>Domain of a function </em>is defined as the set of valid input values that can be given to the function for which the function is defined.

Here, input is time.

We can not have negative values for time.

Therefore, starting value for time will be <em>0 seconds</em>.

And the value of height can not be lesser than that of 0 ft.

$0= 10 - 2t^2\\\Rightarrow 2t^2=10\\\Rightarrow t^2=5\\\Rightarrow t =2.236\ seconds$

Maximum value for time can be 2.236 seconds.

Therefore the domain is:

<em>Interval notation: [0, 2.236]</em>

<em>Set Builder notation: </em> $\{t\ |\ 0\le t\le 2.236\}$

4 0

3 years ago

N/1.6 = 5 what does n equal

FinnZ [79.3K]

N= 8
b/c if u do it backwards 5*1.6=8- you get 8
and to check 8/1.6=5

so n= 5
hope this helps

6 0

3 years ago

In a certain section of Southern California, the distribution of monthly rent for a one-bedroom apartment has a mean of $2,275 a

KATRIN_1 [288]

Answer:

100% probability of selecting a sample of 65 one-bedroom apartments and finding the mean to be at least $2,095 per month

Step-by-step explanation:

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

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score 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 p-value, 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 $s = \frac{\sigma}{\sqrt{n}}$ .