If tan(θ) = cot(40°), what is θ?

What is the exact value of the expression √72 - √8 + √128? Simplify if possible.

emmasim [6.3K]

√72 can be written as 3√8 , √128 as 4√8.. Here, we have to solve √72 -√8 +√128 .. i.e, 3√8 - √8 + 4√8.. which is equal to 6√8 or can be written as 12√2 //

4 0

3 years ago

I need help pleasee please

Volgvan

Answer:

We just have to do 15 ÷ 15/4 = 15 * 4/15 = 4.

7 0

3 years ago

Shane's money is 3:11 if Isabella has 33 dollars how much do shane and Isabella have together

grin007 [14]

3:11
S:I
?:33
So if Isabella has 33 dollars that means they did 11x3=33 so to find Shanes you would do 3x3=9 then add the two together which is $42 hope this helps

3 0

3 years ago

Is y=11x porportional or not

agasfer [191]

Answer:

It is

Step-by-step explanation:

$y=11x\\\frac{y}{x} =11$
The ratio of y to x is always 11, so they are directly proportional

4 0

2 years ago

In your own words, explain the Normal Distribution and provide a real world example.

elena-14-01-66 [18.8K]

Answer:

The Normal distribution is a continuous probability distribution with possible values all the reals. Some properties of this distribution are:

Is symmetrical and bell shaped no matter the parameters used. Usually if X is a random variable normally distributed we write this like that:

$X \sim N(\mu , \sigma)$

The two parameters are:

$\mu$ who represent the mean and is on the center of the distribution

$\sigma$ who represent the standard deviation

One particular case is the normal standard distribution denoted by:

$Z \sim N(0,1)$

Example: Usually this distribution is used to model almost all the practical things in the life one of the examples is when we can model the scores of a test. Usually the distribution for this variable is normally distributed and we can find quantiles and probabilities associated

Step-by-step explanation:

The Normal distribution is a continuous probability distribution with possible values all the reals. Some properties of this distribution are:

Is symmetrical and bell shaped no matter the parameters used. Usually if X is a random variable normally distributed we write this like that:

$X \sim N(\mu , \sigma)$

The two parameters are:

$\mu$ who represent the mean and is on the center of the distribution

$\sigma$ who represent the standard deviation

One particular case is the normal standard distribution denoted by:

$Z \sim N(0,1)$

Example: Usually this distribution is used to model almost all the practical things in the life one of the examples is when we can model the scores of a test. Usually the distribution for this variable is normally distributed and we can find quantiles and probabilities associated

4 0

3 years ago