This is a summary of a student who didn’t know anything about statistics but now understands it! It’s a summary with basic lecture notes with extra added notes to easily understand it better, screenshots and an exam preparation with the answers. Good luck! ;)
Individual closed book exam
• Combination of open and MC questions
o 20 questions
o 16 MC
o 4 open ended
o 1 bonus question
• Understanding of concepts, applying them to questions, interpreting
R output
• No coding!
Exam material:
• Required readings of the textbook and papers
• Lecture slides
Team research project
• Empirical paper
• Data from the pitch project or GALI
• Feedback moments
o Tutorials (questions)
o Peer feedback (submission)
• For more details check out Canvas
,Table of Contents
Lecture 1 .......................................................................................................................... 2
Lecture 2 .......................................................................................................................... 7
Validity: ................................................................................................................................... 7
Reliability .............................................................................................................................. 10
Descriptive statistics or descriptives ....................................................................................... 16
Describing distributions of one variable .................................................................................. 16
Describing relations ............................................................................................................... 19
Fixing omitted variable bias .................................................................................................... 27
Special cases of OLS regressions ............................................................................................. 29
What if our DV is not continuous? .......................................................................................... 34
Hypothesis testing in regression ............................................................................................. 40
Lecture 6 ........................................................................................................................ 47
Moderation & Mediation ....................................................................................................... 49
Mediation .............................................................................................................................. 51
Exam prep ...................................................................................................................... 54
Lecture 1
Quantitative research methods: revolve around answering a particular
research question by collecting numerical data that are analyzed by the
use of mathemethical methods (in particular, statistics)
,Why do we need quantitative research?
- In essence, quantitative research methods provide us with a toolbox
to study the (social) world around us by the use of the scientific
method
- Helps in minimizing cognitive assumptions that may distort our
interpretation
- Depending on the state of prior theory and research on the topic, you
have to use quantitative methods to make a useful contribution to
our understanding of the world
- Only way to establish causal relationships
When do we need it?
Research questions
, Good research questions:
• Can be answered and need answering (”so what?”)
• Improve our understanding of how the world works
• inform theory
Example:
Phenomenon (topic) of interest: Psychological differences between
cultures
(Broad) research question: What is the impact of different forms of
subsitance (e.g., farming, herding) on collectivisms?
• Proposition: a statement or assertion that expresses a belief or idea,
often used as a basis for further reasoning or investigation. E.g. More
interdependent means of subsistence (i.e., farming versus herding)
increase collectivistic mindsets
• Hypothesis: a specific, testable prediction about the outcome of an
experiment or research study. More farmland dedicated to interdependent
rice farming increases measures of cultural thought and nepotism and
decreaes measures of implicit individualism and divorce rates
What is theory
• A theory is an explanation of relationships among concepts or
events
within a set of boundary conditions.
• A (good) theory simplifies and explains complex real-world
phenomena
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