Week 2 RESEARCH METHODS Flashcards
Key components to a statistical investigation are:
Planning the study: ask testable research question & decide how to collect the data
Examining the data: how? Using what graphs?
Reliability: consistency of measure
Validity: degree to which a measure is assessing what it is intended to measure (how much smth is actually testing what it’s supposed to)
Inferring from the data: draw inferences “beyond” the data
Drawing conclusions: based on what you learned, what can you draw?
Cause and effect conclusion: whether one variables changes the other
Distributional thinking
Data varies, so think of meaningful ways to capture that data-
Pattern of variation:
the distribution of the data (how variated it is)
Statistical significance/Significance:
a result is important only if it is unlikely to be caused by chance but rather science
P-value
the amount of probability something might happen (want it to be low, so that it can actually be related to science)
Sample: (DEF)
subset of individuals
Population: (DEF)
large group of individuals that sample came from and represents
Generalized
Conclusions from a sample can be generalized to represent the larger population
Random sample: (DEF)
use probability to select subset of people for a sample
Margin of error: (DEF)
statistic expressing the amount of random sampling error in the results of a survey
Randomly assigning: (DEF)
using probability-based method to divide sample into smaller treatment groups (Balances all variables)
Correlational design
▪ When scientists passively observe and measure phenomena
▪ Do not interfere and change behavior.
▪Identify patterns.
Positive correlation (scatter plot)
variables move together (inr. slope)
as x incr. y incr.
negative correlation (scatter plot)
variables move in opposite directions (dcr. slope)
as x incr. y decr.
Strong VS weak correlation
strong: Higher absolute value
weak: if close to 0 variables are unrelated to eachother
If correlation found, can you assume there is causation?
NO. CORRELATION =/= CAUSATION
Just because 2 variables have a correlation, can’t say they are caused by one other because don’t know which one came first. perhaps confounding variable present.
Experimental design
▪ Researchers measure abstract concepts, like happiness, with operational definitions
▪ Random assignment so participants can choose their conditions
▪ Researchers manipulate independent variable to observe changes in dependent variable
Operational definitions: (DEF)
Should be clear, objective, and specific to be tested and quantified
Confounding variables: (DEF)
other things that affect influences both IV and DV
Examples of cofounding variables
▪ Placebo effect
▪ Experimenter expectations
▪ Participant demand
Double-blind procedure: (DEF)
experimenter nor participant knows participant’s conditions
Qualitative designs:
Allows to study topics that we cant experimentally manipulate.
Observation
often involves researcher embedding self into group- (ex. Wanted to study cult, pretending to be in cult)
Case study
examines specific individuals or contexts
Narrative analysis
studies stories and personal accounts (analyze themes, structures, and dialogues of these narrative)
Quasi- Experimental designs:
▪ does not require random assignment
▪ Subjects assigned to nonrandom groups (e.g. marriages, classes)
▪ Treated as IVs
Longitudinal studies
Def: follows same group of individuals over time
More precise than a survey but quite costly to conduct
Internal validity: (DEF)
make sure results are bc of iv being changed (not biases and not confounds)
External validity: (DEF)
make sure results can be applied to other studies (if post results, people can use them to apply to other situations)
External or Internal validity? which one more important and why?
Internal
Field studies:
doesn’t happen in the lab/in the feild
Ecological validity: (DEF)
rather than being so controlled (in a lab setting) makes the experiment more natural and day-to-day(being in a lab is so controlled, so less likely to happen in real world)
Experience-sampling method: (Studying psychology in the real world)
participants report throughout their day
Diary method: (Studying psychology in the real world)
participants report and have questionnaire at the end of their day
Electronically activated recorder (EAR): (Studying psychology in the real world)
put something in ur ear to record different parts and understand day-to-day experiences
Day reconstruction method (DRM): (Studying psychology in the real world)
obtains info by having participant systematically break down and reflect on
prior day, noting feelings/mood changes of distinct events
Ambulatory assessments: (Studying psychology in the real world)
EEGs, ECGs, sweat tests, and biomarkers all help study physiology in daily lives
Linguistic analyses:
way to extract grammatical and psychological info from a test by counting word frequencies
