1) Consider a binomial distribution with N=10 and p=0.2. Using the terminology in class, how would you describe the shape of this distribution?

-Okay i know its a mound-shaped for sure, but i don't know how to explain why?

2)Consider a sample of size n=35 from the same binomial distribution. What does the Central Limit Theorem tell you about the sampling distribution of x bar ? Include the population mean and standard deviation of the sampling distribution, as well as a description of the shape of the distribution in your answer.

-this one is soo hard! i think the "same binomial distribution" is the N=10 and p=.2 thing.


can anyone please help me thank you!!! sooo soo much.

What's N and P...? Lol.

I'm such a fail. I'm in ap stats too ):

1)
The binomial distribution (gaussian distribution) is generally bell shaped; however, it can be left-skewed, normal and right-skewed =).

N = number of trials / how many times the experiment occurs.
p = chance/probability of success during a single trial.

The equation is given by "N choose x * p^(x) * (1 - p)^(n-x)", n choose x = n! \ x!(n - x)!.

2) Basically, the central limit theorem tells you that your x_bar given more trials/samples will become more normally distributed despite the original distribution graph of samples. A sampling of the distribution of the means. Now write back to me what it means to be normally distributed =).

i.e. you have like 2 trials and your data looks like a [][][][]. Just a straight line. Increase N, and you will slowly get a normal distribution shape =o.