stats Flashcards
(30 cards)
Z score
z = (X – μ) / σ
discrete uniform distribution
all probabilities are the same
random variable
a variable whose value depends on the outcome of a random event
discrete random variable
the value can only take certain numerical values
in a normal distribution, how much data is within 1 standard deviation of the mean
68%
in a normal distribution, how much data is within 2 standard deviations of the mean
95%
in a normal distribution, how much data is within 3 standard deviations of the mean
99.7%
binomial distribution set notation
X ~ B(n, p)
normal distribution set notation
X ~ N(μ, σ^2)
requirements for binomial distribution
2 possible outcomes
fixed probability of success
trials are independent of each other
simple random sampling method
assign every unit in the population a unique random number, then select numbers at random, then select the units that correspond to those numbers
systematic sampling method
give every member of the population unique, sequential numbers, then select a start number randomly then select every nth person where n = population size / sample size
quota sampling method
set a quota for each category then perform opportunity sampling in each category until that category’s quota is met
cluster sampling method
divide the population into clusters, such that every member of the population is in exactly one cluster in a random or representative way. Then, we randomly select clusters to sample. For a one stage cluster we then use every member of the selected clusters in our sample. For a two stage cluster we randomly sample within the selected clusters to get our final sample.
opportunity sampling
Opportunity or convenience sampling is a sample based on what is convenient for the sampler. For example, it could be a survey handed out to the friends and family of the sampler.
stratified sampling method equation
size of category in sample=
size of population /
size of category in population
×total sample size
stratified sampling method once in categories
simple random sampling
two conditions under which the normal distribution may be used as an approximation to the binomial distribution
n is large
p is close to 0.5
why might a normal distribution not be appropriate
if 3 standard deviations away from the mean is negative
standard deviation formula notation
(∑(x-μ)^2)/n-1
census
measures every number of a population
sampling frame
list of all units
strata
group of population
normal distribution point of inflection
μ-σ or μ+σ
