ECONOMETRICS INTRO (L0&L1) Flashcards

1
Q

Descriptive statistics

A

Using mean,variance and correlation etc to help us understand the affect of variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Forecasting

A

Predicting future outcomes eg interest rates

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Estimating

A

How much one variable will affect another

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

Big data

A

How we analyse huge/complex data sets

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Properties of big data

A

Volume
Variety
Velocity
Veracity

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Volume

A

Large no of observations/variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Variety

A

Different forms data comes in (video,text)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Velocity

A

How quick data can be recorded eg facebook posting

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Veracity

A

The quality of the data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

(A+B)’ (transposed)

A

A’+B’

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

(A’)’ (transposed)

A

A

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

(KA)’ (transposed)

A

KA’

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

(AB)’ (transposed)

A

B’A’

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Square matrix

A

Rows=columns, can’t find the inverse for any other type

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Symmetric matrix

A

Transposed=not transposed A’=A

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Inverse matrix

A

A x A’ = I
BA=AB=I
If the matrix has an inverse it’s invertible/non-singular

17
Q

(A-1)-1

A

A

18
Q

(A’)-1

A

(A-1)’

19
Q

(AB)-1

A

B-1A-1

20
Q

(BA)-1

A

A-1B-1

21
Q

((AB-1))’

A

(AB’)-1=(B’A’)-1=(A’)-1(B’)-1

22
Q

|A’|

A

|A|

23
Q

|AB|

A

|A|B|

24
Q

|KA|

A

K^n |A|
Where n is the number of rows/columns

25
Q

Collinearity

A

The rows and columns are the same so the determinant is 0
(12
12)

26
Q

A is invertible when…

A

The determinant does not equal 0, also means the rank= number of rows

27
Q

Orthogonal

A

Xi’xj=0

28
Q

Rank(AB)

A

If the rank isn’t equal of matrix A or B, then use the lower rank

29
Q

Tr(A’)

A

Tr(A)

30
Q

Tr(A+B)

A

tr(A)+tr(B)

31
Q

Tr(AB)

A

Tr(BA) if they’re square matrices (cyclicity of trace)

32
Q

Tr(KA)

A

Ktr(A)

33
Q

A is positive definite if

A

The quadratic is >0

34
Q

A is positive semidefinite if

A

The quadratic is >_0

35
Q

A is negative definite if

A

The quadratic is <0

36
Q

A is negative semidefinite if

A

The quadratic is <_0

37
Q

Symmetric matrix properties

A

Positive definite, non singular
Semidefinite if det(A) and tr(A) are positive If A has a positive determinate, then A^k will also be positive

38
Q

Idempotent

A

A^2=A eg Identity matrix