CH 2 Research Methods (Terms) Flashcards
Naturalistic Observation
Type of Observational Research
Watching behaviour in a real-world setting without trying to manipulate the situation.
Participation Observation
Type of Observational Research
The observer becomes apart of the group or social setting being studied
Case Study
An in-depth analysis of an individual, social unit, event, or some other phenomenon.
Survey
Uses questionnaires to gather information about people
- Self-report measure
- Examine traits, beliefs, opinions, and feelings
- Can be descriptive/ used to test hypotheses
e.g., Personality Traits, Beliefs about distracted driving, Depression.
Correlation Design
A research design that examines the extent to which two variables are associated.
- A statistical association between variables
- Scores are associated in a non-random fashion
- Only measures things.
Experiment
Researcher:
- Manipulates one or more variable
- Attempts to control extraneous factors
- Measures how the manipulated variable affects participant’s responses
Participants are randomly assigned to groups or orders of conditions.
Population
Refers to all the cases or observations of interest in a survey research
Sample
A subset of cases or observations from the population in a survey research
Representative Sample
Reflects the important characteristics of the population in a survey research
Random Selection
A procedure that ensures that every person in a population has an equal chance of being chosen to participate
Reliability
Consistency of a measurement tool
- Measures can be reliable but inaccurate
Types
- Test-retest
- Interrater Reliability
Validity
The extent to which a measure assesses what it purports to measure
Key concept
Variables are measured not manipulated
Positive correlation
As X increases, Y increases
As X decreases, Y decreases
Negative Correlation
As X increases, Y decreases
As X decreases, Y increases
No (Zero) Correlation
No association between variables
Pearson’s R
A statics that measures the direction and strength of the linear relationship between two variables
Scatterplot
A graph that portrays the intersection of data on two variables for a single individual
Illusory Correlation
The perception of statistical association between two variables when none exists
Independent Variable
The variable manipulated by the researcher
Dependent Variable
The response that is measured, to determine whether the independent variable has produced an effect
- The presumed effect in the cause and effect relationship
Random Assignment
Participants in the experiment are randomly sorted into groups
Experiment Group
The group of participants that receives the manipulation
Control Group
The group of participants that does not receive the manipulation
Between-Participants Design
A.K.A Between-Subjects
- Researcher randomly assigns people to different groups
- Each participants takes part in only one condition of the experiment
Random Assignment: Randomly assigned to different groups
Within-Participants Design
A.K.A Within-Subjects
- Each participant acts as their own control
- Each participants engages in every condition of the experiment
Counterbalancing: Randomly assigned order of conditions.
Confounding Variable
Any variable that differs between the different groups (conditions) of the experiment besides the manipulated variable.
Placebo Effect
Improvement resulting from the mere expectation of improvement.
- Countered with Blinded Experiments
Blinded Experiments
Participants are unaware if they are in the experimental group or control group.
- Used to counter the Placebo Effect
Nocebo Effect
Harm resulting from the mere expectation of harm.
Experimenter Expectancy Effects
Researcher’s hypotheses lead them to unintentionally bias the outcome of a study
- Countered with Double Blind Experiments
Demand Characteristics
- Cues that participants pick up from a study that allow them to generate guesses regarding the researcher’s hypotheses
- Can affect responses; Participants may behave the way they think they are expected to behave
- Counteract with “cover” stories and distractor tasks
Double Blind Experiments
When neither the researchers nor the participants are aware of who is the experimental or control group.
Ethics
Represent a system of moral principles and standards.
Research Ethics Board (REB)
An independent institutional committee that evaluates whether proposed research projects with human participants complies with the TCPS-2 principles and guidelines.
Tri-Council Policy Statement (TCPS-2)
Mandate: “To promote research that is conducted according to the highest ethical standards.”
Core Principles:
- Respect for Persons
- Concern for Welfare
- Justice
Respect for Person
Respect autonomy & protect those with developing, impaired, or diminished autonomy.
Concern for Welfare
Quality of life (financial, etc.); physical and mental health
Justice
Fair and equitable treatment
Informed Consent
Informing research participants of what is involved in a study before asking them to participate
- The principle that people have the right to make a voluntary informed decision about whether to participate in a study.
Deception
Researchers intentionally withhold information from (passive) or intentionally mislead (active) participants about the nature of the study.
Debriefing
A conversation or communication with the participant that conveys additional information about the study.
- Provide complete information about the purpose of the study
- Give the participants a chance to ask questions
- Minimize negative effects/feelings
Animal Research as a Ethical Issue
Is the knowledge gained worth the suffering?
- Animals give us important “models” to learn from
- Some research may not generalize
Questions around the use of animals in research are complex, it is important to keep the context in mind
Descriptive Statistics
Numerical characterization that describe data
Inferential Statistics
Mathematical methods that allow us to determine whether we can generalize findings from our sample to the full population.
Statistical Significance
- Unlikely to be due to chance alone
- Conventional threshold is 5/100 or p (probability) < 0.05
- Does not equal practical significance as large samples can lead to statistically significant results
Central Tendency
Measures the “typical”/”central” scores in a data set.
e.g., Age in a university class: 18, 20, 22, 22, 23
Mean
The average of the dataset
- Advantage: Includes all numerical information in dataset
- Disadvantage: Heavily influenced by outliers
Median
The middle score in the data set.
Mode
The more frequently occurring score in the dataset.
Variability (Dispersion)
Measures of how scores vary
- How loosely or tightly bunched the scores are
Range
Difference between the highest and lowest scores
