The phrase "4 more than twice a number" becomes '2n + 4'.

Given the lengths of the sides which of the following would NOT be a right triangle?

zmey [24]

• 9.12.16
&
• 33,45,55

5 0

2 years ago

Which of the following is a common characteristic of a binomial distribution?

Tanya [424]

Answer:

E. Each trial is independent

Step-by-step explanation:

I'm not completely sure why all binomial distribution trials are independent, but there are requirements for binomial distributions.

These requirements are:

- Each outcome is either a success (p) or a failure (Q)

- All trials are independent

- There are a fixed number of "n" trials

- The probability of success (p) is the same for each trial

I also just took the test and got this right.

6 0

2 years ago

Tasha bought some bracelets that cost $5 each and 2 hats that cost $12 each. The cost of her total purchase was $39

Mazyrski [523]

Answer:

27

Step-by-step explanation

If your trying to find the bracelets

3 0

3 years ago

I’m trying to get a lot of my geometry done. Please help.

Nataliya [291]

Answer:

do the work first. and u will get the answer easily.

6 0

3 years ago

Rockwell hardness of pins of a certain type is known to have a mean value of 50 and a standard deviation of 1.2.a. If the distri

zalisa [80]

Answer:

a

$P(\= X \ge 51 ) =0.0062$

b

$P(\= X \ge 51 ) = 0$

Step-by-step explanation:

From the question we are told that

The mean value is $\mu = 50$

The standard deviation is $\sigma = 1.2$

Considering question a

The sample size is n = 9

Generally the standard error of the mean is mathematically represented as

$\sigma_x = \frac{\sigma }{\sqrt{n} }$

=> $\sigma_x = \frac{ 1.2 }{\sqrt{9} }$

=> $\sigma_x = 0.4$

Generally the probability that the sample mean hardness for a random sample of 9 pins is at least 51 is mathematically represented as

$P(\= X \ge 51 ) = P( \frac{\= X - \mu }{\sigma_{x}} \ge \frac{51 - 50 }{0.4 } )$

$\frac{\= X -\mu}{\sigma } = Z (The \ standardized \ value\ of \ \= X )$

$P(\= X \ge 51 ) = P( Z \ge 2.5 )$

=> $P(\= X \ge 51 ) =1- P( Z < 2.5 )$

From the z table the area under the normal curve to the left corresponding to 2.5 is

$P( Z < 2.5 ) = 0.99379$

=> $P(\= X \ge 51 ) =1-0.99379$

=> $P(\= X \ge 51 ) =0.0062$

Considering question b

The sample size is n = 40

Generally the standard error of the mean is mathematically represented as

$\sigma_x = \frac{\sigma }{\sqrt{n} }$

=> $\sigma_x = \frac{ 1.2 }{\sqrt{40} }$

=> $\sigma_x = 0.1897$

Generally the (approximate) probability that the sample mean hardness for a random sample of 40 pins is at least 51 is mathematically represented as

$P(\= X \ge 51 ) = P( \frac{\= X - \mu }{\sigma_x} \ge \frac{51 - 50 }{0.1897 } )$

=> $P(\= X \ge 51 ) = P(Z \ge 5.2715 )$

=> $P(\= X \ge 51 ) = 1- P(Z < 5.2715 )$

From the z table the area under the normal curve to the left corresponding to 5.2715 and

=> $P(Z < 5.2715 ) = 1$

So

$P(\= X \ge 51 ) = 1- 1$

=> $P(\= X \ge 51 ) = 0$

5 0

2 years ago