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Quantitative Methodologies

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Quantitative Methodologies Matthew Schwarz and Valerie Dao Fulbright Research Mentorship Program Ho Chi Minh City, Vietnam Introduction Quantitative research – PowerPoint PPT presentation

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Title: Quantitative Methodologies


1
Quantitative Methodologies
  • Matthew Schwarz and Valerie Dao
  • Fulbright Research Mentorship Program
  • Ho Chi Minh City, Vietnam

2
Introduction
  • Quantitative research
  • Quantify variation
  • What factors influence athletic ability?
  • Predict relationships
  • When is it most likely to rain?
  • Describe characteristics
  • What is the average height of an FRMP student?

3
Bridging the Gap
  • Qualitative Understand a certain phenomenon
  • Is my understanding generalizable?
  • Qualitative Determine whether your understanding
    can be generalized

4
Review
  • Review
  • What is a variable?
  • Independent variable?
  • Dependent variable?
  • How are independent and dependent variables
    related?
  • What does it mean to operationalize a variable?
  • Bonus Questions
  • Can you have multiple independent variables?
  • Can you have multiple dependent variables?

5
What is the Operational Definition of Pho?
6
Steps
  • Define your research question
  • Why are there more foreign businesses in HCMC
    than Hanoi?
  • Define your variables
  • Independent variable Location (HCMC or Hanoi)
  • Dependent variable Factors influencing decision.
  • Operationalize your dependent variable
  • Labor supply
  • Business-friendly authorities
  • Others?
  • Collect data
  • Survey
  • Databases
  • Analyze relationship using statistical methods

7
Correlation and Causation
  • What is correlation?
  • Correlation means that there is a relationship
    between two variables.
  • What is causation?
  • Causation means that one variable causes another
    variable to occur.

8
Correlation and Causation
  • If there is correlation isnt there
    automatically causation?
  • Lets look at some examples and see if we can
    answer this question.

9
Finance
  • Research question
  • What factors cause stock prices to increase?
  • Variables
  • Independent Price
  • Dependent (1) Earnings
  • Hypothesis
  • When a company reports strong earnings, its
    stock price tends to increase.
  • Correlation?
  • Causation?

10
Politics
  • Research question
  • What was the most important reason why Barack
    Obama won the 2008 election?
  • Variables
  • Independent Vote for Obama?
  • Dependent (1) Democrat
  • Dependent (2) Intelligent
  • Hypothesis
  • The most important reason why Barack Obama won
    the 2008 election was his status as a Democrat.
  • Correlation?
  • Causation?

11
Medicine
  • Research question
  • Does this pill improve health?
  • Variables
  • Independent Took pill?
  • Dependent (1) Health
  • Hypothesis
  • Taking this pill makes people healthier.
  • Correlation?
  • Causation?

12
Correlation does not imply causation
  • By now, you should understand that correlation
    does not imply causation.
  • There are two main reasons why we cannot assume
    causation even when we observe correlation
  • Coincidence
  • Intervening variables

13
Coincidence
  • Even if we observe a strong correlation between
    two variables, we cannot be sure that its not a
    coincidence.
  • Always ask yourself this question
  • Am I confident that the dependent variable is
    changing because of changes in the independent
    variable?

14
Intervening Variables
  • Intervening or confounding variables prevent us
    from credibly providing causality.
  • An intervening variable is a variable that
    influences both the dependent and independent
    variable.

15
Which one is the Intervening Variable?
16
Spurious Relationships
The intervening variables cause spurious
relationships. Spurious relationships are when
are when two variables seem to have a connection
due to a third unknown or unseen (intervening)
variable.
17
Spotting Intervening Variables
  • Lets revisit our examples to see if we notice
    any intervening variables.

18
Finance
  • In the Finance example, we saw a correlation
    between a companys earnings and its stock price.
  • Are there any intervening variables?

19
Politics
  • In the Politics example, we saw a correlation
    between voting for Obama and status as a
    Democrat.
  • Are there any intervening variables?

20
Medicine
  • In the Medicine example, we saw a correlation
    between taking the pill and feeling healthier.
  • Are there any intervening variables?

21
Dealing with Intervening Variables
  • The way to move from correlation to causation is
    by controlling for intervening variables.
  • This requires the researcher to modify his/her
    statistical model.

22
Survey Design
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