Eksamenssett.no
Ressurser
Skolenytt
Hoderegning
MRK 3460
Formelark
Markedsanalyse
eksamenssett.no
Deskriptiv statistikk
•
x
ˉ
=
∑
x
i
n
\displaystyle \bar{x} = \frac{\sum x_i}{n}
x
ˉ
=
n
∑
x
i
•
s
2
=
∑
(
x
i
−
x
ˉ
)
2
n
−
1
\displaystyle s^2 = \frac{\sum(x_i - \bar{x})^2}{n-1}
s
2
=
n
−
1
∑
(
x
i
−
x
ˉ
)
2
•
s
=
s
2
s = \sqrt{s^2}
s
=
s
2
•
z
=
x
−
x
ˉ
s
\displaystyle z = \frac{x - \bar{x}}{s}
z
=
s
x
−
x
ˉ
•
C
V
=
s
x
ˉ
×
100
%
\displaystyle CV = \frac{s}{\bar{x}} \times 100\%
C
V
=
x
ˉ
s
×
100%
•
I
Q
R
=
Q
3
−
Q
1
IQR = Q_3 - Q_1
I
QR
=
Q
3
−
Q
1
Utvalg og feilmargin
•
S
E
=
s
n
\displaystyle SE = \frac{s}{\sqrt{n}}
SE
=
n
s
•
E
=
z
⋅
p
(
1
−
p
)
n
\displaystyle E = z \cdot \sqrt{\frac{p(1-p)}{n}}
E
=
z
⋅
n
p
(
1
−
p
)
•
n
=
z
2
⋅
p
(
1
−
p
)
E
2
\displaystyle n = \frac{z^2 \cdot p(1-p)}{E^2}
n
=
E
2
z
2
⋅
p
(
1
−
p
)
Hypotesetesting
•
t
=
x
ˉ
−
μ
0
s
/
n
\displaystyle t = \frac{\bar{x} - \mu_0}{s/\sqrt{n}}
t
=
s
/
n
x
ˉ
−
μ
0
(ett utvalg)
•
t
=
x
ˉ
1
−
x
ˉ
2
s
1
2
/
n
1
+
s
2
2
/
n
2
\displaystyle t = \frac{\bar{x}_1 - \bar{x}_2}{\sqrt{s_1^2/n_1 + s_2^2/n_2}}
t
=
s
1
2
/
n
1
+
s
2
2
/
n
2
x
ˉ
1
−
x
ˉ
2
(to utvalg)
•
χ
2
=
∑
(
O
−
E
)
2
E
\displaystyle \chi^2 = \sum \frac{(O - E)^2}{E}
χ
2
=
∑
E
(
O
−
E
)
2
•
d
=
x
ˉ
1
−
x
ˉ
2
s
p
\displaystyle d = \frac{\bar{x}_1 - \bar{x}_2}{s_p}
d
=
s
p
x
ˉ
1
−
x
ˉ
2
(Cohens
d
d
d
)
•
KI:
x
ˉ
±
t
α
/
2
⋅
s
n
\displaystyle \bar{x} \pm t_{\alpha/2} \cdot \frac{s}{\sqrt{n}}
x
ˉ
±
t
α
/2
⋅
n
s
Regresjon
•
Y
=
β
0
+
β
1
X
+
ε
Y = \beta_0 + \beta_1 X + \varepsilon
Y
=
β
0
+
β
1
X
+
ε
•
R
2
=
1
−
S
S
r
e
s
S
S
t
o
t
\displaystyle R^2 = 1 - \frac{SS_{res}}{SS_{tot}}
R
2
=
1
−
S
S
t
o
t
S
S
res
•
Justert
R
2
=
1
−
(
1
−
R
2
)
(
n
−
1
)
n
−
k
−
1
\displaystyle R^2 = 1 - \frac{(1-R^2)(n-1)}{n-k-1}
R
2
=
1
−
n
−
k
−
1
(
1
−
R
2
)
(
n
−
1
)
•
V
I
F
j
=
1
1
−
R
j
2
\displaystyle VIF_j = \frac{1}{1-R_j^2}
V
I
F
j
=
1
−
R
j
2
1
•
F
=
R
2
/
k
(
1
−
R
2
)
/
(
n
−
k
−
1
)
\displaystyle F = \frac{R^2/k}{(1-R^2)/(n-k-1)}
F
=
(
1
−
R
2
)
/
(
n
−
k
−
1
)
R
2
/
k
Faktoranalyse
•
KMO
>
0,6
> 0{,}6
>
0
,
6
for akseptabel faktoranalyse
•
Eigenverdi
>
1
> 1
>
1
(Kaiser-kriteriet)
•
Faktorladning
∣
λ
∣
>
0,5
|\lambda| > 0{,}5
∣
λ
∣
>
0
,
5
•
h
2
=
∑
λ
j
k
2
\displaystyle h^2 = \sum \lambda_{jk}^2
h
2
=
∑
λ
jk
2
(communality)
Reliabilitet
•
α
=
k
k
−
1
(
1
−
∑
s
i
2
s
t
o
t
a
l
2
)
\displaystyle \alpha = \frac{k}{k-1}\left(1 - \frac{\sum s_i^2}{s_{total}^2}\right)
α
=
k
−
1
k
(
1
−
s
t
o
t
a
l
2
∑
s
i
2
)
(Cronbachs alfa)