Psyc312 Exam1

• Tenacity
• Authority
• Experience
• Empirical Evidence

• Systematic or formal observaion to obtain objective, reliable, valid and quantitative measures of the matter of interest.
• By itself, empiricism CANNOT explain WHY

Example: All As are Bs. C is an A, therefore C is a B.

A syllogism is only valid if it obeys the rules of logic. Valid logic enables very strong truth claims GIVEN the empirical validity of the premises.

• belief bias
• conversion errors
• confirming evidence bias

Rationalism: used to develop theories and hypotheses and way to test.

Empiricism: the means of conducting the tests.

• 1. Objectivity
• 2. Replication
• 3. Self-Correction
• 4. Control

• Two meanings:
• 1. Directly manipulating the variable of interest
• 2. Controlling for unwanted variables that could influence the results.

This is essential to draw conclusions about cause and effect.

Subject Variables: individual differences in participants such as age, gender, IQ, ethnicity.

Quasi-independent variables: variables outside of the participant that the researcher cannot manipulate, such as weather, laws, geographical location.

Other unwanted, uncontrolled factors that could influence the dependent variable. Confounds which invalidate the experiment.

• Set of procedures for reducing large masses of data to manageable proportions in order to draw conclusions from those data.
• Two types: Descriptive and Inferential.

Descriptive: Numbers that summarize a set of data.

Inferential: Calculations that determine whether an IV has a significant effect; they allow us to draw inferences.

The complete set of events being studied. It is the entire group to which we want to generalize the results.

Numerical values summarizing population data.

The subgroup of the population that we collect data from.

A sample in which each member of the population has an equal chance of inclusion in the study.

Participants selected for their accessibility or ease of testing.

Everyone in the study has an equal chance of being assigned to each of the study groups.

Continuous data (aka "measurement" or "quantitative" data). A mean can be determined.

Categorical (aka "frequency" or "count" data). No mean is possible.

• Nominal
• Ordinal
• Interval
• Ratio

(they go from simple to complex)

• N = total sample size
• n = number of participants per group

X = set of scores for one variable

• Respect for the Dignity of Persons
• Responsible Caring (competence)
• Integrity in Relationships (honesty)
• Responsibility to Society

• Privacy
• Confidentiality
• Informed Consent
• No harassment or degrading comment
• No unjust discrimination
• Fair compensation

• Protect welfare of others, avoid harm
• Take responsibility for actions
• Keep up to date
• Referral for help
• Maintain appropriate relationships
• Pilot studies

• No dishonest, fraud or misrepresentation in reporting results
• Do not supress disconfirming evidence
• Acknowledge limitations of findings
• Do not deceive if not necessary
• Debriefing
• No coercive enticement to participate

• Contribute to discipline and state of knowledge
• Keep informed
• Critical self-evaluation
• Educate & promote scientific growth of others
• Respect for social customs, cultural expectations
• Sensitive to needs of society when designing research (hot topics)

• Respect for Human Dignity (cardinal principle)
• Respect for Free and Informed Consent
• Respect for Vulnerable Persons
• Respect for Privacy and Confidentiality
• Respect for Justice and Inclusiveness
• Balance of Harms and Benefits

Explanation of purpose of study, methods used, correct misconceptions, ask if any questions

• Education: What was the study about?
• Dehoaxing: Describe deceptions and why?
• Desensitizing: Any psychological discomfort?

• To determine the current state of the knowledge
• Provide a basis for hypotheses
• Guide you in selecting paradigm, operational definitions

• Step 1: Develop a research question
• Step 2: Survey the literature
• Step 3: Build a hypothesis

• Synthetic statement: is either true or false
• Falsifiable: can be shown to be wrong
• Can be stated in "General Implication Form" (if...then...)
• Can be directional (more/less than) or non-directional (different from)

Deductive: General to specific; How we form our research hypotheses

Inductive: Specific to general; Combining the results of several studies into a theory

• physiological (manipulation of biological state)
• experience (manipulation of amount/type of training/learning)
• stimulus/environmental (manipulation of the environment)
• participant (manipulation of aspects of participant)

• correctness
• rate/frequency
• degree or amount
• latency or duration

• Unwanted variables that increase the variability of all scores within groups
• Affects ALL groups
• Makes the effect harder to see

• Unintended influences on the DV
• biases result in a particular direction
• renders findings MEANINGLESS

• Step 1: Randomization
• Step 2: Elimination (of extraneous variables)
• Step 3: Constancy (across all groups of participants)
• Step 4: Balancing (equal distribution of extraneous variables)

• When the position in a series affects how participants respond.
• Doesn't depend on the EVENT but on the POSITION
• think fatigue/practice/learning

• When the effects of one event influences responses to the next event.
• Depends on the EVENT not the POSITION
• (i.e., previous drug intake)

works to counteract carryover and order effects:

• 1: Each event must be presented to each participant an equal number of times.
• 2: Each event must occur an equal number of times at each session.
• 3: Each event must precede and follow each of the other events an equal number of times.

• True score (hypothetical concept); and
• Error (bias and random error)

Observed score = True Score + Error (bias + random)

• Random error: noise, temp., time of day.
• Bias error: experimenter characteristics or experimenter expectancies (Rosenthal)

• Use standardized methods
• Replication

• Standardization
• Objectivity
• Single-blind research

Random participant error: carelessness, distraction

Participant Bias: Demand characteristics, Good Participant effect, response bias

Features of an experiment that seem to inadvertently cause participants to act in a particular way.

Tendency for participants to behave as they think the researcher wants them to behave.

• Condcut double-blind research
• Use deception

• Yea- and Nay-sayers.
• When the context affects participant response
• Can be a factor of the experimental setting or the questions
• Social desirability can be an issue

• Include "agree" and "disagree" items
• Randomize question presentation.
• Pilot testing

• Random observer error: carelessness, distraction
• Observer/scorer bias: confirmatory bias

More important to reduce observer bias (confound) than random error (nuisance).

• Eliminate human observer (use mechanical measure to reduce random and bias errors)
• Limit observer subjectivity (focus on observable behavior, standardized coding)
• Make observer blind

• Does the manipulation or measure ACTUALLY represent the claimed construct?
• Reliability
• Content validity
• Convergent validity
• Discriminant or divergent validity

• assess random error
• reliability is a prerequisite for validity
• Test-retest reliability
• Inter-rater reliability
• Internal consistency

• measure of participant random error
• variability across items = random error
• Index calculated using Cronbach's Alpha, split-half correlation and average inter-item correlation

• Is the measure's content relevant to the concept?
• Does it clearly relate to the concept?
• Does it cover all aspects of the concept?

Does measure correlate with other indicators of the same construct?

Is the measure distinguishable from other constructs?

• Sensitivity is the ability of measures to detect effects.
• "does your measure minimize the influence of error?"
• Use measures with maximal validity and maximal reliability
• Avoid restriction of range, all or nothing measures.
• Add scale points to a rating scale
• Pilot test measure

• Naturlistic research settings;
• manipulation not possible
• natural variation
• prediction and selection
• temporal change
• comparing size of associations

• Archival research
• Observational techniques such as case studies,
• naturalistic observation,
• participant observation
• clinical perspective

• Limits generalization
• may have missing data values
• may not be ideal to your research question
• cannot show causation

• client chooses clinician, whereas participant observer chooses others to study
• clinicians cannot be unobtrusive or passive
• Participant observer's goal is understanding whereas clinician's goal is helping

• Reactivity: when the knowledge of being watched affects behavior, aka "The Hawthorne Effect"
• High on external validity but low on internal validity
• Cannot make cause-effect statements
• objectivity

Descriptive surveys seek to determine what % of the population have particular characteristics, beliefs or behaviors.

Analytic surveys seek to determine the relevant variables and how they are related.

• Most common estimate of test reliability
• measures how well a group of items measure one uni-dimensional construct
• should be at least 0.7

• surveys/questionnaires: examine an opinion
• tests/inventories: assess a specific attribute, characteristic or ability of the subject

• content validity
• concurrent validity
• criterion validity: can the test predict future behavior?

• test-retest consistency
• split half consistency

• Random sampling; or
• Stratified random sampling: the population is separated into different subgroups and a random sample is taken from each

• Single-strata: select from a subgroup of the population
• Cross-sectional: multiple subgroups at the same time
• Longitudinal: one cohort over an extended period of time

• An attempt to capture the complexity of human behaviour in its natural environment.
• INDUCTIVE

philosophical position that stresses observable facts and seeks universal laws

both quant and qual research concerned with the collection of observed information but NOT universal laws.

Attempts to use qualitative methods to identify themes and build a theory.

• both a statistical technique and a research method
• research designed to determine whether an association exists between 2 variables