Unit 0 - Research Design

Hypothesis

Tentative explanation that must be falsifiable (able to be supported or rejected)

Operational Definition

Clear, precise, quantifiable definition of your variables — allows replication and collection of reliable data

Qualitative Data

Descriptive Data (eye color)

Quantitative Data

Numerical data — IDEAL and necessary for statistics

Population

Everyone the research could apply to

Sample

The people (or person) specifically chosen for your study

Correlation

Identify relationship between two variables

Directionality Problem

Which direction does the correlation go?

3rd Variable Problem

Different variable is responsible for the relationship

Positive Correlation

Variables increase and decrease together

Negative Correlation

As one variable increases the other decreases

Experiments

Purposefully manipulate variables to determine cause/effect

Independent Variable

Purposefully altered by researcher to look for effect

Experimental Group

Received the treatment; can have multiple of these

Control Group

Placebo/baseline; can only have one

Dependent Variable

Measured variable (depends on the independent variable)

Placebo Effect

Any observed effect on a behavior that is “caused” by the placebo

Double-Blind Procedure

Experiment where neither the participant nor the experimenter are aware of which condition people are assigned to

Single-Blind Procedure

Only participant blind — used if experimenter can’t be blind

Confound

Error/flaw in study that is accidentally introduced

Random Assignment

Assigns participants to either control or experimental group at random — increases the chance of equal representation among groups

Naturalistic Observation

Observe people in their natural setting

Case Study

Studies ONE person (usually) in great detail

Meta-analysis

Combines multiple studies to increase sample size and examine effect sizes

Descriptive Statistics

Show shape of the data

Mean

Average (normal distribution)

Median

Middle Number (skewed distribution)

Mode

Number that occurs most often

Bimodal Distribution

Has two modes — usually indicates good bad scores

Negatively Skewed

Mean is to the left; Mode is to the right

Positively Skewed

Mean is to the right; Mode is to the left

Range

Distance between smallest and biggest #

Standard Deviation

Average amount the scores are spread from the mean (bigger # = more spread)

Inferential Statistics

Establishes significance (meaningfulness)

Statistical Significance

Results are not due to chance, explains manipulation caused the difference in means

Effect Size

Data has practical significance

Ethical Guidelines

Confidentiality, informed consent, informed assent, debriefing, deception must be warranted, no harm

Surveys

Usually turned into correlation — subject self reports and may be prone to bias

Social Desirability

People lie to look good

Wording Effects

How you from your questions can impact your answers

Random Sample (selection)

Method for choosing participants where everyone has a chance to take part (increases generalizability)

Representative Sample

Sample mimics the general population

Convenience Sample

Select participants on availability (less representative and generalizable)

Sampling Bias

Sample isn’t representative

Cultural Norms

Behaviors of a particular group that can influence research results

Experimenter bias/Participant bias

Experimenter/participant expectations influence the outcome

Cognitive Bias

Bias in thinking/judgement

Confirmation bias

Find information that supports our preexisting beliefs

Hindsight Bias

“I knew it all along”

Overconfidence

Overestimate our knowledge and abilities

Hawthorne Effect

People change behavior when watched