Answer:

Step-by-step explanation:

Firstly, we've to interchange the variables.

Solving for y

Adding 3 to both sides

Multiplying 2 to both sides

Taking cosine on both sides

Dividing both sides by y

Replace y by 
=> 
Answer:
The probability that the sample proportion will be greater than 13% is 0.99693.
Step-by-step explanation:
We are given that a large shipment of laser printers contained 18% defectives. A sample of size 340 is selected.
Let
= <u><em>the sample proportion of defectives</em></u>.
The z-score probability distribution for the sample proportion is given by;
Z =
~ N(0,1)
where, p = population proportion of defective laser printers = 18%
n = sample size = 340
Now, the probability that the sample proportion will be greater than 13% is given by = P(
> 0.13)
P(
> 0.13) = P(
>
) = P(Z > -2.74) = P(Z < 2.74)
= <u>0.99693</u>
The above probability is calculated by looking at the value of x = 2.74 in the table which has an area of 0.99693.
Step-by-step explanation:
Where is the graph Buddy?????
Answer:
i have autism and adhd and add and dmdd so plz dont yell at me that i did not answer it!!!
Step-by-step explanation:
Answer:
5.9 years.
Step-by-step explanation:
Central Limit Theorem
The Central Limit Theorem establishes that, for a normally distributed random variable X, with mean
and standard deviation
, the sampling distribution of the sample means with size n can be approximated to a normal distribution with mean
and standard deviation
.
For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.
For a proportion p in a sample of size n, the sampling distribution of the sample proportion will be approximately normal with mean
and standard deviation 
In this question:
Mean of the population is 
If a sampling distribution is created using samples of the ages at which 69 children begin reading, what would be the mean of the sampling distribution of sample means?
By the Central Limit Theorem, the same population mean, of 5.9 years.