Econometric - Lecture 2

Econometric - Lecture 2

University

5 Qs

quiz-placeholder

Similar activities

Blood - 1

Blood - 1

University

10 Qs

CHS Toxicology

CHS Toxicology

9th Grade - University

10 Qs

Java set3

Java set3

University

10 Qs

RESISTENCIA DE MATERIALES

RESISTENCIA DE MATERIALES

University

10 Qs

CORTO REPOSICION INMUNO 2, 2023

CORTO REPOSICION INMUNO 2, 2023

University

5 Qs

Quiz 2 Primer Corte

Quiz 2 Primer Corte

University

10 Qs

Farmacologia SNC

Farmacologia SNC

University

10 Qs

p53

p53

KG - University

7 Qs

Econometric - Lecture 2

Econometric - Lecture 2

Assessment

Quiz

Other

University

Medium

Created by

Elya Nabila

Used 2+ times

FREE Resource

5 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is not a diagnostic checking?

Heteroscedasticity

Autocorrelation

Multicollinearity

Demean

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following techniques to test the autocorrelation?

White test

Breusch-Pagan LM test

Ramsey Reset test

Jarque-Bera test

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is the correct inference for log-linear model?

1 unit change in X will induce a β2 unit change in Y

1 percent change in X will induce a β2/100 unit change in Y

1 unit change in X will induce a 100β2 percent change in Y

1 percent change in X will induce a β2 percent change in Y

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is correct about the correlation?

Correlation measures the strength of the linear relationship between two variables.

The correlation between two random variables is a dimensionless number between 1 and -1.

Correlation misses nonlinearities completely.

All of the above.

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which one is correct about the causality?

Bidirectional :  ‘x’ being a cause of ‘y” but “y” is not being a cause of “x” (x à y) (y x)

Unidirectional :  ‘x’ being a cause of ‘y” and “y” is being a cause of “x” (x y)

Neutral : ‘x’ is not being a cause of ‘y” and “y” is not being a cause of “x”

Causality cannot be used for time series.