Idea: Number of observations that are free to vary after sample mean has been calculated. It increases variation and therefore also standard deviation extremely when n is small and approximates n when n is getting bigger.
What are discrete probability distribution and what are the rules?
Recap: Discrete variables à Variables producing outcomes that come from a counting process.
A fixed number of observations, n
e.g. 15 tosses of a coin
e.g. 10 light bulbs taken from a warehouse
Constant probability for the event of interest occurring (π) for each observation
e.g. Probability of getting a tail is the same each time we toss the coin.
Each observation is categorized as to whether the “event of interest” occurred or not.
e.g. head or tail in each toss of a coin
e.g. defective or not defective light bulb
When the probability of the event of interest is represented as π, then the probability of the event of interest not occurring is 1 – π.
Observations are independent
The outcome of one observation does not affect the outcome of the other
negatively skewed (LS) when p > 0,5; Symmetric when n = 10 and p = 0,5 and prositively skewed (RS) when p < 0,5