Answer: The probability distribution for the number of cells in the third generation is a Binomial distribution.
Step-by-step explanation:
We use binomial distribution when we have repeated process and the outcome is either a success or a failure.
The probability of success. P ( probability of dying). The probability of failure q ( probability of splitting into two).
The formula for binomial distribution is : n combination x multiplied by p raised to power x multiplied by q raised to power n-x.
Answer:
(-1,2)
Step-by-step explanation:
Answer:
s = 6
Step-by-step explanation:
8(s+3) = 72
Expand the brackets out:
(8 x s) + (8 x 3) = 72
8s + 24 = 72
Now you get rid of 24 on the left, by taking away 24. But you also have to do the same on the right side so that both sides are equal:
8s + 24 = 72
left(-24) = right (-24)
So that leaves you with:
8s = 48
Now divide both sides by 8 to make them equal and to get s on its own:
8s = 72
left(/8) = right (/8)
Therfore:
s = 6
0.4 grams or 0.40 grams however you like writing decimals, but either way they are both the same.
Answer:
The sampling distribution of the sample proportion of adults who have credit card debts of more than $2000 is approximately normally distributed with mean
and standard deviation 
Step-by-step explanation:
Central Limit Theorem
The Central Limit Theorem estabilishes 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:

Then

By the Central Limit Theorem:
The sampling distribution of the sample proportion of adults who have credit card debts of more than $2000 is approximately normally distributed with mean
and standard deviation 