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Full summary Behavioral research methods I: designing research premaster (0HP00) (0HP00) $7.50   Add to cart

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Full summary Behavioral research methods I: designing research premaster (0HP00) (0HP00)

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Summary of 17 pages for the course Behavioral research methods I: designing research premaster at TUE (Full Exam Summary)

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  • July 20, 2021
  • 17
  • 2020/2021
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BRM Summary
Module 1 Course Overview
Variables, are features/characteristics of something of someone
Cases, are that thing or someone

Variables can be unidimensional or multidimensional
- Unidimensional; represented as a straight line
o I count the number of coffees I drink on a day
- Multidimensional; represented in two or more dimensions
o My coffee has both a temperature and an intensity
Variables can be dependent or independent
- Dependent; variable that depends on another variable
- Independent; logically prior to the dependent variable
- e.g. Lecture attendance influences final grades
o Dependent; Course grade
o Independent; Lecture attendance
Variables can be qualitative or quantitative
- Qualitative describe descriptive information
o I drink coffee everyday
- Quantitative describe numerical information
o I drink 4 coffees every day (discrete)
o I drink 80 grams of coffee everyday (continuous)

e.g. football players

Variables / Cases Player 1 Player 2 Player 3
Goals scored 0 2 12
Age 18 22 32
Height 188 190 177

Cases could also be teams, companies or countries
Variables needs to vary!!!
If for example you examine all Spanish football teams, the country they’re based in is a constant

Distinguish levels of measurement
Difference (Ranking) Order Similar Example
Intervals
Categorical Nominal Yes No No City of football
teams
Categorical Ordinal Yes Yes No Order in
competition
Quantitative Interval Yes Yes Yes Age (age of 0
doesn’t mean
there’s no age
Quantitative Ratio Yes Yes Yes Body height
(meaningful 0
point)

,Discrete Number
- Set of separate numbers
o Number of goals scored (because you cannot score 1,3 goals)

Continuous Number
- Infinite region of values
o Height of players, (can be 1,764252…)

A unit of analysis is the object of interest
- This can be a person, a school, a group of people, or a country

Validity is the accuracy and trustworthiness of instruments, data, and findings in research
- Does it measure what you want
- Only make claims about the date you gathered

Reliability, whether you get the same result when measuring multiple times
- How many siblings do you have? – reliable
- How much is your house worth? – unreliable




Reliable No Yes No Yes
Valid No No A little (on average) Yes

Reliability:
- Inter-rater reliability
o measure of consistency between two or more independent raters (observers) of the
same construct.
- Test-retest reliability
o measure of consistency between two measurements (tests) of the same construct
administered to the same sample at two different points in time.
o Is the score consistent when measured on different times (e.g. IQ test should be)
- Split-half reliability
o Measure of consistency between two halves of a construct measure.
o For instance, if you have a ten-item measure of a given construct, randomly split
those ten items into two sets of five (unequal halves are allowed if the total number
of items is odd), and administer the entire instrument to a sample of respondents.
- Internal consistency reliability
o a measure of consistency between different items of the same construct.
o People’s score on items should be correlated with each other

, (Construct) Validity
- Translational validity
o how well the idea of a theoretical construct is translated into or represented in an
operational measure
- Criterion-related validity
o how well a given measure relates to one or more external criterion, based on
empirical observations
- Convergent validity
o the closeness with which a measure relates to (or converges on) the construct that it
is purported to measure,
- Discriminant validity
o the degree to which a measure does not measure (or discriminates from) other
constructs that it is not supposed to measure
- Face validity
o whether an indicator seems to be a reasonable measure of its underlying construct
“on its face”.
o Does the measure make sense?
- Content validity
o how well a set of scale items matches with the relevant content domain of the
construct that it is trying to measure

Precision is about the number of decimal points in a measurement
Accuracy refers to the difference between the measured value and the true value

Cause-effect is true if:
- two variables co-vary; as scores for one increase or decrease, scores for the other also
decrease or increase
- covariation is not spurious; there is no third variable
- logical time order
- There must be a theory, explanation

Good theories are ideas that have held up against challenges (attempts of falsification), and that
explain new phenomena as they come up


Module 2: Research Philosophies
Socrates - Problems are solved by breaking them down into a series of smaller questions
Plato - Objects of knowledge must be attained through reason alone
Aristotle – Observation is crucial for understanding the world and the human mind
Leonardo Da Vinci - His approach to science was one of intense observation and detailed recording
Sir Isaac Newton - most influential scientists’ theory of gravitation by watching the fall of an apple
Charles Darwin - all species of life have descended over time from common ancestors

Rationalism vs Empiricism
- Rationalism is the idea that human beings achieve
knowledge because of their capacity to reason
- Empiricism states that the only knowledge that human
beings acquire is from sensory experience
Empirical cycle or
Newtons hypothetico-deductive model of science →

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