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Cheatography

stats formula sheet Cheat Sheet (DRAFT) by

stats final cheat sheet

This is a draft cheat sheet. It is a work in progress and is not finished yet.

Basic Terms

parameter
fixed value describing popula­­tion; usually unknown
statistic
value calculated from sample; used to estimate parameter
descri­ptive stats
- collec­ting, summar­izing, describing data
- graphi­cal­/nu­merical
infere­ntial stats
- drawing conclu­sio­ns/­making predic­tions about pop based on sample
**

data types

name
type
data
discrete
num
whole number
continuous
num
decimals
nominal
cat
no order
ordinal
cat
has order

sampling

 

graphical summary

 

numerical summary

percentile
quartile
standard deviation
IQR
outliers
 
symmetric
skewed
measure of center
mean
median
measure of spread
SD
IQR

histograms

 

associ­ation

 

probab­ility

 

interp­ret­ation

 

properties

 

condit­ional probab­ility

 

discrete RV

 

binomial RV

 

cont. RV

 

cont prob distri­bution properties

 

empirical rule

 

z stuff

 

normal distri­bution

 

sampling distri­bution - sample mean

 

CLT

 

standard error and bias of X̅

 

estimation of μ

 

margin of error

 

confidence level & z-score

 

Confidence Interval - 3 cases

1. pop not normal; σ KNOWN ⇒ central limit theorem
the approx confidence interval for pop mean μ is
x̅±z*(­σ/√n)
z*=zα/2 is upper critical value
2. pop normal; σ UNknown ⇒ t-dist­rib­ution
T≡ (X̅-μ)­/(S/√n)
S²=1/n­-1∑­(Xi­-X̅)²
S=√S²

t stuff

 

estimator and MOE from CI

 

sampling dist. - sample proportion

 
 

hyp test for one population proportion

 

hyp test - one population mean μ

normal pop, known σ
one sample z-test
normal pop, UNknown σ
one sample t-test

decision errors

type 1
-reject a true Ho
-false positive
type 2
-fail to reject false Ho
-false negative
relati­onship
α
prob of type 1 error (same as sig level)
β
prob of type 2

hypothesis test steps

1. check validity of assump­tions
a. randomness
b. sample size
c. population distri­bution
2. set up hypotheses
- identify parameter of interest
3. test statistic and its distri­bution
4. compute p-value
- confirm level of sig given in advance
5. conclusion interp­ret­ation

1. validity

 

2. hypotheses

3. test statistic

4. p-value

5. conclusion

 
 

hypothesis test

or signif­icance testing
test an assumption regarding pop. parameter
method used depends on kind of data and reason
asses plausi­bility of hypothesis using sample data

hypothesis testing terms

hypothesis
a claim or statement about a charac­ter­istic of a population of interest
null hypothesis
statement about the value of a population parameter, such as the population mean (µ) or the population proportion (p)
alt hypothesis
claim to be tested, the opposite of the null hypothesis
test statistic
value computed from the sample data that is used in making a decision about the rejection of the null hypoth­esis; converts the sample mean (x̄) or sample proportion (p̂) to a Z- or t-score under the assumption that the null hypothesis is true;
p-value
area under the curve to the left or right of test statistic; compared to level of signif­icance (α)
critical value
signif­icance level
statis­tical signif­icance
practical signif­icance
effect size
degree of a relati­onship between two given variables
standa­rdized effect size
one sided
two sided
tests whether the population parameter is equal to, versus not equal to, some specific value