

Study with the several resources on Docsity
Earn points by helping other students or get them with a premium plan
Prepare for your exams
Study with the several resources on Docsity
Earn points to download
Earn points by helping other students or get them with a premium plan
Community
Ask the community for help and clear up your study doubts
Discover the best universities in your country according to Docsity users
Free resources
Download our free guides on studying techniques, anxiety management strategies, and thesis advice from Docsity tutors
Number of observations in sample. 3.1. N. Number of observations in population. 3.1 x x-‐bar x = xi ! n. Sample mean. 3.1 μ mu. Population mean.
Typology: Study notes
1 / 2
This page cannot be seen from the preview
Don't miss anything!
Section Symbol Name Formula (if relevant) Description
3.1 n Number of observations in sample
Number of observations in population
x
x-‐bar
x =
x
i
n
Sample mean
μ
mu Population mean
3.1 M Median M =
n + 1
2
th
smallest observation
“Middle” observation
mode
Most frequent observation
Min
Minimum
Min = Smallest Observation Smallest observation
3.2 Max Maximum
Max = Largest Observation
Largest observation
Range R = Max! Min
s
2
s
2
x
i
! x
2
n! 1
Sample variance
s or s
x s = s
2
Sample standard deviation
2
sigma squared Population variance
! or!
x
sigma Population standard deviation
x value! mean
standard deviation
Z-‐score for a given x value
1
1
25
100
th
smallest observation First quartile
3
3
75
100
n + 1
th
smallest observation Third quartile
3
1
Inter quartile range
3.4 UF Upper Fence
3
Upper limit for outliers
Lower Fence
1
Lower limit for outliers
4.1 r Correlation coefficient
a
Slope of linear regression model
4.2 b Intercept of linear regression model
y y-‐hat
y = ax + b Predicted response value
residual
residual = y!
y
Observed y – Expected y
r
2
Coefficient of determination
5.1 E Event space
Sample space
Number of observations in the set X
Probability of event E
!
Z sub alpha
Z-‐score that has! area to the right of it
μ
x
Mu sub x-‐bar
μ
x
= μ
Population mean of sampling distribution
!
x
Sigma sub x-‐bar
!
x
!
n
Population standard deviation of sampling distribution
p
Proportion of population with given attribute
8.2 x Number of sample with given attribute
p p-‐hat
p =
x
n
Proportion of sample with given attribute
μ
p ˆ
mu sub p-‐hat
μ
ˆ p
= p
Population mean of sample proportion
ˆ p Sigma sub p-‐hat !
ˆ p
p ( 1 " p )
n
Population standard deviation of sample proportion
! / 2
T sub alpha/2 T-‐score the has! / 2 area to the right of it
df df = n! 1
Degrees of freedom
0
H naught Null hypothesis
1
H one Alternative hypothesis
μ
0
mu naught Population proportion assuming H
0
is true
p p! value Probability of a result as extreme if H
0
is true
T T! score
x value! mean
sample standard deviation
T-‐ Score for a given x value
p
0
p naught Population proportion assuming H
0
is true
d
d bar
Sample mean of difference
s
d
s sub d Sample standard deviation of difference (dependent)
μ
d
mu sub d Population mean of difference
s
d
s sub d s
d
s
1
2
n
1
s
2
2
n
2
Sample standard deviation of difference (independent)
p
p =
x
1
2
n
1
2
Pooled sample proportion
p ˆ
1
" p ˆ
2
ˆ p 1
"
ˆ p 2
p 1 "
n
1
n
2
Population Standard Deviation of proportion difference
(assuming H
0
is true)
ˆ p 1
"
ˆ p 2
ˆ p
1
" ˆ p
2
p
1
1 " p
1
( )
n
1
p
2
1 " p
2
( )
n
2
Population Standard Deviation of proportion difference
(for confidence intervals)