Statistics
2
variable
explanatory
- ·
jo
=
predicator
variable
= outcome >
-
response
expectations >
- write statistical analysis on the assignments + exam
, ·Lecture 1 INFORDETAR & WAY AXIONA
:
-
# testing
-
>
-
used for GROUP COMPARISON
-Single sample +-test >
-
compare the means to a fixed value
>
-
comparing one group to a known or expected number (a baseline)
Example :
dataset could be higher or
lower M mean in the example given
column =
in the
↓ d ↓
Code : to test /data accuracy ,
alternative "two. sided"
,
5 lecture
mu =
0 .
( we are interested
in whether the score is from 50 %
assessing accuracy
the data
given on each
person's accuracy
Independent samplect-test >
->
compare the means of two independent groups
>
-
comparing two
groups who have completed the same task
Example :
Ho :
Mgroupi
=
UGroupe Ha MGroup 1>lGrOup2
:
Code + test/accuracy
:
d
~
musicality
d data-dat
, ,
alternative =
"greater")
column du column in dataset
, Paired +- test (DEPENDENT)
>
-
compare pairs of values
>
-
compare repeated tasks completed by the same person
>
- used to compare two sets of data from the same individuals (paired)/
Example :
dependent values
Code : to test /accuracy - 1
, accuracy - 2
, paired =
TRUE alternative =
"greater" (
,
d
↓
column accuracy column accuracy
task 1 task 2
A
-
go
>
-
comparing
InIOMMICHION E ANONA
group MEANS
↓
ANalysis Of Variance AQUA =
↳ 3 groups
7
&
/ the null
Type error :
rejecting
-
hypothesis when it is actually true ·
jo
i
↳
S J
·
either no error happens or at least 1 error happens
the smaller the p-value is the MORE we confident we are in
the results (confidence range is bigger)
P- 0 . 05 - statistically significant
, -
:
VARIABLE TYPES
-2-way ANOVA
ANOVA =
special case of a liner regression (LR)
↳ disuse
-
in favor of GR
↳
the state of not being used "but it can still be found in literature
-
·
jo
1)
-
WY ANDNA
>
- it can also be
e1 =
12 + 13
or
at least 2 means
11 + M2 =
M3
differ
2
variable
explanatory
- ·
jo
=
predicator
variable
= outcome >
-
response
expectations >
- write statistical analysis on the assignments + exam
, ·Lecture 1 INFORDETAR & WAY AXIONA
:
-
# testing
-
>
-
used for GROUP COMPARISON
-Single sample +-test >
-
compare the means to a fixed value
>
-
comparing one group to a known or expected number (a baseline)
Example :
dataset could be higher or
lower M mean in the example given
column =
in the
↓ d ↓
Code : to test /data accuracy ,
alternative "two. sided"
,
5 lecture
mu =
0 .
( we are interested
in whether the score is from 50 %
assessing accuracy
the data
given on each
person's accuracy
Independent samplect-test >
->
compare the means of two independent groups
>
-
comparing two
groups who have completed the same task
Example :
Ho :
Mgroupi
=
UGroupe Ha MGroup 1>lGrOup2
:
Code + test/accuracy
:
d
~
musicality
d data-dat
, ,
alternative =
"greater")
column du column in dataset
, Paired +- test (DEPENDENT)
>
-
compare pairs of values
>
-
compare repeated tasks completed by the same person
>
- used to compare two sets of data from the same individuals (paired)/
Example :
dependent values
Code : to test /accuracy - 1
, accuracy - 2
, paired =
TRUE alternative =
"greater" (
,
d
↓
column accuracy column accuracy
task 1 task 2
A
-
go
>
-
comparing
InIOMMICHION E ANONA
group MEANS
↓
ANalysis Of Variance AQUA =
↳ 3 groups
7
&
/ the null
Type error :
rejecting
-
hypothesis when it is actually true ·
jo
i
↳
S J
·
either no error happens or at least 1 error happens
the smaller the p-value is the MORE we confident we are in
the results (confidence range is bigger)
P- 0 . 05 - statistically significant
, -
:
VARIABLE TYPES
-2-way ANOVA
ANOVA =
special case of a liner regression (LR)
↳ disuse
-
in favor of GR
↳
the state of not being used "but it can still be found in literature
-
·
jo
1)
-
WY ANDNA
>
- it can also be
e1 =
12 + 13
or
at least 2 means
11 + M2 =
M3
differ
