Week 2: Research Methods Flashcards
Statistical Thinking, Research Designs, Conducting Psychology Research in the Real World
Key Components to a statistical investigation…
PLANNING THE STUDY - asking a testable research question & deciding how to collect data
EXAMINING THE DATA - determine appropriate ways to examine data; relevant graphs, descriptive statistics, patterns in data, individual observations that deviate from overall patterns - what does it reveal? - is there evidence for reliability/validity
INFERRING FROM THE DATA - what are the valid statistical methods for drawing inferences “beyond” data you collected
DRAWING CONCLUSIONS - based on what you’ve learned from data, what conclusions can you draw and who do they apply to; can you draw a cause-and-effect conclusion about your treatments?
Reliability
Refers to the consistency of a measure
Validity
The degree to which a measure is assessing what it is intended to measure
Cause-and-Effect
Related to whether we say one variable is causing changes in the other variable, versus other variables that may be related to these two variables
Distribution
The pattern of variation in data
2 Fundamental aspects of statistical thinking
DATA VARY - values of a variable vary
Analyzing the pattern of variation (DISTRIBUTION of the variable) often reveals insights
Level of Significance
A result is statistically significant if it is unlikely to arise by chance alone
Compare the p-value to the cut-off value
If p-value is smaller than cut-off value, we REJECT the hypothesis that only random chance is at play
P-value
Probability of observing a particular outcome in a sample, or more extreme, under a large conjecture abt the larger population/process
The LOWER the P-VALUE the HIGHER the STATISTICAL SIGNIFICANCE
Sample
Collection of individuals on which we collect data
Population
Larger collection of individuals that we would like to generalize our results to
Generalized
Related to whether the results from the sample can be generalized to a larger population
Random Sample
Using a probability-based method to select a subset of individuals for the sample from the population
Margin of Error
Expected amount of random variation in a statistic; often defined for 95% confidence
Key to the margin of error - When we use a probability sampling method, we can make claims abt how often the sample result would fall within a certain distance from the unknown population value by chance alone
Random Assignment
Using a probability-based method to divide a sample into treatment groups
Tends to balance out all the variables
Critical to experimentation bc if the only difference between two groups is the independent variable, we can infer the independent variable is the cause of any observable difference
Random Sampling/Assignment
Sampling - paramount to generalizing results from our sample to a larger population
Assignment - key to drawing cause-and-effect conclusions
Probability models help us assess how much random variation we can expect in our results in order to determine whether our results could happen by chance alone & to estimate a margin of error
Operational Definitions
How researchers specifically measure a concept
Psychologists measure many abstract concepts, such as happiness/intelligence, by beginning w operational definitions of the concepts
Independent Variable
Variable the researcher manipulates and controls in an experiment
Cause
Dependent Variable
Variable the researcher measures but does not manipulate in an experiment
Effect
Confounds
Things that could undermine your ability to draw casual inferences
Expectations that can influence you in a study
Ex. placebo effect, participant demand (participants try to behave in a way they think the experimenter wants them to), experimenter observation
Placebo Effect
sometimes a person just knowing that he or she is receiving special treatment or something new is enough to actually cause changes in behaviour or perception
Double-Blind Procedure
Neither the participant nor the experimenter knows which condition the participant is in - don’t know what’s going on
Because both parties are “blind” to the condition, neither willff be able to behave in a way that introduces a confound
Correlational Research
When scientists passively observe and measure phenomena - we do not intervene/change behaviour; we identify patterns of relationships but typically can’t infer what causes what; can only examine TWO variables at a time
Correlation
Measures the association between two variables, or how they go together
CORRELATION DOES NOT MEAN CAUSATION
Correlation Coefficient
Association between two variables can be summarized statistically using the CC (r); provides information abt the direction & strength of the association between two variables
Positive correlation - two variables go up/down together in a scatterplot - dots form a pattern that extends from bottom left to upper right - r value indicated by a POS number
Negative correlation - two variables move in opposite directions (one up one down) - r value indicated by a negative number
Strength of a correlation: WEAK - has to do w how well the two variables align - many exceptions; low absolute value close to 0 STRONG - few exceptions; tighter dots; high absolute value
Qualitative Designs
Participant observation, case studies, narrative analysis
Allow us to investigate harder to study topics that we can’t experimentally manipulate
Participant Observation - involves researcher embedding them self into a group in order to study its dynamics; typically aware that a researcher is aware to study them
Case Study - involves an intensive examination of specific individuals or specific contexts - Freud did this a lot; brain injuries (round of tests)
Narrative Analysis - centres around the study of stories/personal accounts of people, groups, or cultures; analyze the themes, structure, and dialogue of each person’s narrative - examine people’s personal testimonies in order to learn more abt the psychology of those individuals/groups; allows researcher not only to study WHAT the participant says, but HOW; studying how perspectives are conveyed
Quasi-expiremental design
An experiment that does not require random assignment to conditions - rely on existing group memberships; treat these as the independent variables even though we don’t assign people to the conditions and don’t manipulate the variables - casual inference is more difficult
Ex. married people might differ on a variety of characteristics from unmarried people; if we find married participants are happier than single participants, it’ll be hard to say marriage causes happiness bc the married might have already been happier than people who remained single
Random assignment is what makes experimental designs stronger, while quasi-experiments are more like observing things as they already are.
Longitudinal study
A study that follows the same group of individuals over time
ex. 20,000 Germans for two decades - psychologist Rich Lucas able to determine that people who end up getting married indeed start off a bit happier than their peers who never marry
Longit studies like this provide valuable evidence for testing many theories in psych, but they can be costly, especially if they follow many people for years
Surveys
Way of gathering information using old-fashioned questionnaires/the Internet - can reach a larger number of participants at a much lower cost; can be used for correlational and experimental research
Internal Validity
The degree to which a cause-effect relationship between two variables has been unambiguously established
External Validity
The degree to which a finding generalizes from the specific sample and context of a study to some larger population and broader settings
Ecological Validity
The degree to which a study finding has been obtained under conditions that are typical for what happens in everyday life
Field Studies
In order to make claims abt human behaviour that apply across populations/environments, researchers complement traditional lab research w field research where the psychological. lab is brought to participants
Allow for the important test of how psychological variables and processes of interest “behave” under real-world circumstances (what ACC does happen rather than what CAN happen); can facilitate “downstream” operationalizations of constructs that measure life out comes of interest DIRECTLY rather than indirectly
Research Methods for Studying Daily Life
- Studying Daily Experiences - collect in the moment self-report data directly from people as they go about their daily lives; asking participants repeatedly over a period of time to report on current thoughts/feelings; location, social environment, activity, experiences; gold standard for studying daily life; allowed researchers to do research that’s more externally valid/more generalizable to real life than the traditional lab experiment
- Studying Daily Behaviour - experience sampling used (ex. daily social interactions, activities); equip participants w a portable audio recorder EAR programmed to periodically record brief snippets of ambient sounds - recorder provides researchers w a series of sound bites that, together, amount to an acoustic diary of participants’ days; naturalistic observation can be used to study objective aspects of daily behaviour/how it can yield findings quite different from other methods; time-lapse photography, analyzed personal spaces and garbage
- Studying Daily Physiology - researchers interested in how our bodies respond to fluctuating demands of our lives; ambulatory physical monitoring (monitoring physiological reactions as people go abt their daily lives); ambulatory assessment of hormones; researchers can use ambulatory physiological monitoring to study how the little experiences in our lives leave objective, measurable traces in our bodily systems
- Studying Online Behaviour - how people act/interact w others on internet; researchers beginning to think of virtual behaviour as serious as “actual” behaviour and seek to make it a legit target of their investigations; study virtual language behaviour; bound to change social science
- Smartphone Psychology - what’s next; smartphones will become devices for scientific data collection/intervention; immense potential for data collection also brings w it big new challenges for researchers (e.g., privacy protection, data analysis, synthesis); collecting usage data
Experience-Sampling method
Methodology where participants report on their momentary thoughts, feelings, and behaviours at different points in time over course of a day
Ecological Momentary Assessment
An overarching term to describe methodologies that repeatedly sample participants’ real world experiences, behaviour, & physiology in real time
Diary Method
Methodology where participants complete a questionnaire abt their thoughts, feelings, and behaviour of the day at the end of the day
Day Reconstruction Method (DRM)
Methodology where participants describe their experiences & behaviour of a given day retrospectively upon a systematic reconstruction on the following day
Developed to obtain info abt a person’s daily experiences w/o going thru the burden of collecting momentary experience-sampling data; reporting on a given day after engaging in a systematic, experiential reconstruction of the day on the FOLLOWING day
Electronically Activated Recorder (EAR)
Methodology where participants wear a small, portable audio recorder that intermittently records snippets of ambient sounds around them
White Coat Hypertension
Phenomenon in which patients exhibit elevated blood pressure in the hospital or doctor’s office but not in their everyday lives
Ambulatory Assessment
Overarching term to describe methodologies that assess the behaviour, physiology, experience, & environments of humans in naturalistic settings
Linguistic Analyses
A quantitative text analysis methodology that automatically extracts grammatical and psychological information from a text by counting word frequencies
Full-Cycle Psychology
Scientific approach whereby researchers start w an observational field study to identify an effect in the real world; then followup w lab experimentation to verify effect & isolate causal mechanisms; return to field research to corroborate experimental findings
Dynamic give-and-take between lab and field research
