Vocab III Flashcards
Do you use Z or T for proportions in hypothesis testing?
always use Z for proportions, we assume the proportion is normally distributed so to check use: n(p’) > 5 & n(1-p’) > 5
how do we find the critical value for proportion hypothesis testing?
go to the t-table and look for either the one-tail or two tail then go all the way down to the z
when do we use the F distribution?
the F distribution is used when comparing variances, not averages
how can one preform a F-testing?
-normally distributed
- independent of each other
what does this mean?
Ho: σ1^2 = σ2^2
Ha: σ1^2 ≠ σ2^2
either the population has equal variances or unequal variances
how do you find the other side for the F-distribution CV when the ?
we divide the cv (1/CV)
what is Poisson distribution?
is a discrete probability distribution that expresses the probability of a given number of events occurring in a fixed interval of time or space.
Poisson distribution symbols
e:
λ:
x:
!:
-is a constant(remains that symbol throughout solving)
-landa, historic average(number we are given)
-is the number of times we are interested on
-factorialy
is the mean of the sampling distribution ever going to be exactly the mean of the population?
NO
central limit theorem
is how we are able to make conclusions about a population, even if we do not know the true mean
type I error
occurs when you reject a good null hypothesis when it was true
type II error
occurs when you don’t reject the null hypothesis when it was false
hypothesis testing
the most important statistical test. involves collecting data from a sample and evaluating it. this is how a decision is made using the evidence
what is a sampling distribution
is a probability distribution of a statistic that is obtained through repeated sampling of a specific population
key words for Ha: when it is >
greater than
more than
bigger than
key words for Ho: when it is ≤
less than or equal to
is at most
key words for Ha: when it is <
less than
fewer than
smaller than
key words for Ho: when it is ≥
greater than or equal to
is at least
key words for Ha: when it is ≠
not equal
differs
not the same as
is different than
statistics
is the study of how to collect, organize, analyze, and interpret numerical information from data
parameter statistics
is a numerical measure that describes an aspect of a population
sample statistic
is a numerical measure that described an aspect of a sample
descriptive statistic
involved methods of organizing, picturing, and summarizing info from samples of populations
inferential statistics
involves methods of using information from a sample to draw conclusions regarding the population
standard deviation
provides a measure of the overall variation in a data set
-will be small when the data are all concentrated close to the mean, showing little variation or spread
-will be larger when the data values are more spread out from the mean, showing more variation
methods of assigning probabilities
classical, relative frequency, subjective
rules for assigning probabilities
probability must be between 0 & 1
if all events are mutually exclusive (meaning an event can only be in one category total probabilities added up must = 1)
sampling errors
non responsive bias
selection bias
halo effect
respondent error
sample methods
simple random
judgement
quota
stratified random
convenience
cluster
systemic
snowball
