Other terms

Question 1

Reproducibility

Answer 1

Whether the same result can be produced by using a different coding/analysis (SAME research method) and conducted by a different researcher (essentially two different tests measuring the same outcome)

Question 2

Repeatability/Replicability

Answer 2

Whether the same result can be produced by replicating the same experiment but by different researcher

Question 3

What is true causation?

Answer 3

True causation can only be established when necessity and sufficiency criteria are satisfied

Question 4

Necessary

Answer 4

Y is necessary, but not sufficient to cause X

Question 5

Sufficiency

Answer 5

Y alone is both necessary and sufficient to cause X

Question 6

Population

Answer 6

A target group that contains a common characteristic that you want to research about

Question 7

Sample

Answer 7

A small portion taken from a target group to conduct study on

Question 8

Sample statistics

Answer 8

Characteristics about the sample
-> can be used to infer population parameter

Question 9

Population parameter

Answer 9

Characteristics about the population

Question 10

Differences between quantitative vs. qualitative research

Answer 10

Quantitative:
- use statistics
- usually through survey, observation, experiment
- use to test or confirm a hypothesis
- usually need lots of participants

Qualitative:
- use words and meaning
- usually through interview
- use to understand a theory
- usually don’t need lots of participants

Question 11

Construct

Answer 11

refers to a concept or characteristic that can’t be directly observed but can be measured by observing other indicators that are associated with it.
(e.g. description or diagnosis of depression)

Question 12

Theory

Answer 12

a collection of statements that together attempt to describe and explain a set of observed phenomena
-> usually provide a model to explain
-> makes general prediction

Question 13

Hypothesis

Answer 13

a prediction made based on the theory of the observed phenomenon

criteria:
- falsifiable
- testable
- precisely stated
- rational
- parsimonious

Question 14

Variables

Answer 14

any characteristic that can assume multiple values (i.e. can vary)

those that researchers manipulate or measure in experiment

need to be operationalized to measure

Question 15

Confounding variable

Answer 15

a type of extraneous variable that can directly affect the DV instead of IV
(disproportionately affect one level of the IV more than the other

can result in us measuring:
- an effect of the IV on the DV when it is not present
- no effect of the IV on the DV when it is present

Question 16

Extraneous variable

Answer 16

a type of variable that if failed to be controlled by experiment, can affect the DV measurement

Question 17

Replication crisis

Answer 17

Methodological crisis in which the
results of studies were not
reproducible when tested again.

Question 18

Benefits of open science

Answer 18

• Accumulation of knowledge
• Increased citation of work
• More media coverage
• Support meta-research practice

Question 19

Open Science

Answer 19

The act of sharing research to the public (unrestricted public access)

Question 20

APA open science conduct code

Answer 20

require researchers to be willing and able to make data available for 5 years after publication

What to share:
- Data
- Protocols
- Code for experiments and analyses

Benefit:
- Verification of methods
- Analytics Reproducibility

Question 21

Pre-registration to publish

Answer 21

Researchers encouraged to submit plans for the specific research questions that they wish to address, and the analyses they will conduct prior
to data collection

Question 22

What are good principles to conduct reproducible analysis?

Answer 22

• Provide clear annotations of what documents are
• Store original data files separately
• Record all steps of data processing
• Use open source software where possible

Question 23

Steps to Induction

Answer 23

1. Evidence from observations
2. Conclusion is drawn
3. Generate theories
   -> can go on to test this

Question 24

Hypothetical-deductive methods

Answer 24

1. Theory taken from induction (observation and intuition)
2. Form hypothesis
3. Using empirical tests
4. Gain results
   -> supported: uphold hypothesis
   -> unsupported: refined or abandon hypothesis

Question 25

Bayesianism

Answer 25

• answer to induction and falsification
• involves calculating and updating probabilities as new information becomes available to make the best possible predictions.

Question 26

Falsifiability

Answer 26

• answer to the problem with induction
• for a theory to be scientific, it has to be falsifiable (aka can be proven false by scientific methods)

Question 27

What are the 5 characteristics of a good scientist?

Answer 27

1. Uncertain
2. Skeptical
3. Open-minded
4. Cautious
5. Ethical

Question 28

Relational/correlational research

Answer 28

• Study the correlation between 2 variables.
• Ideal for gathering data quickly from natural settings -> can generalize your findings to real-life situations
• Cannot test for causal-links
• Use when conducting experiment are not possible (e.g. unethical)

Question 29

Descriptive research

Answer 29

• research aim to identify characteristics, frequencies, trends, and categories.
• does not control or manipulate any variable
• common: observation, survey, case studies

Question 30

Construct vs. Variable

Answer 30

Construct is defined by theoretical definition (hard to observe or test)

Variable is defined by operational definition (easy to test)

Question 31

Sample size

Answer 31

• Size matters!
• Sampling error can result if your sample is not large enough
• Trade off between size and time/cost
• Factors in deciding on sample size: design, response rate, heterogeneity of population

Question 32

Random error

Answer 32

chance fluctuations in our measurement -> obscure the result (make less precise/accurate)

Question 33

Systematic error

Answer 33

a bias is present and influencing our
measurement in a systematic way
-> bias the result