Exam 1 Flashcards

Why do we study a scientific approach to Psychology?

Why do we study a scientific approach to Psychology?

- Attributes of scientific thinking in psychology.
- Origins of scientific thinking.
- The goals of research psychology.

Hard (Natural) vs Social Sciences

Hard Sciences: Physics, Chemistry, Astronomy, Geology.

Social Sciences: Psychology, Sociology, Anthropology, Economics, Political Science

Both: explanation, understanding, and predictability through observation and experimentation.

Why do we study psychology?

To understand human behavior; To understand ourselves as individuals; To understand others; Interventions: counseling, family therapy, risky behaviors, education (in school), training (on the job), political psychology.

other psychology courses are about ________, but research methods is about _______.

content; process

epistemology

The theory of knowledge, especially the methods, validity, and scope of knowing. An understanding of what differentiates justified belief from opinion.

Pros and Cons of Logic and Reasoning in Research Methods

Use of reason via conversation [discourse] to come to a consensus; Uses the a priori method based on argument and logic, not direct experience denoting conclusions derived from premises or principles

Problems: our initial assumptions may be incorrect by using reason/logic alone, we have no way to check the accuracy of our assumptions valid logical arguments can lead to opposite conclusions

Pros and Cons of Empiricism/Direct Experience in Research Methods

Learning via direct observation or experience

Problems: experiences are limited to our interpretations of them experiences can be influenced by social cognition biases (confirmation bias, belief perseverance, availability heuristic)

Determinism

Is our behavior pre-determined?

Objectivity

Eliminating any bias from our own experimentation. Other researchers should be able to verify our results through replication.

Five Goals of Research in Psychology

Predict: psychological events follow certain “laws” that are regular and therefore predictable
Explain: psychological events are explained in terms of their relationship to other factors (causal explanations are ideal)
Apply: science informs real-world applications of psychological events
Describe: identify regularly occurring sequences of psychological events (e.g., behaviors, thoughts, emotions, etc.)
Influence Behavior: Learning; early intervention; rehabilitation, socialization, and training, self-acceptance; marketing; avoiding risky or dangerous behaviors;

(PEADI)

Three Main Goals of Psychology as a Science

- Psychology is a science and adheres to the assumptions and goals of science
- Science distinguishes itself from pseudoscience by being systematic, empirical, data-driven, tentative, and falsifiable
- As psychological scientists, we strive to describe, predict, explain, and apply what we discover from our research.

its science; science is real, science follows PEADI

Five general principles in the Code of Conduct

- Beneficence and Nonmaleficence: constantly weigh costs & benefits; protect from harm; produce for greatest good
- Fidelity and Responsibility: be professional; constantly be aware of responsibility to society
- Integrity: be scrupulously honest
- Justice: always treat people fairly
- Respect for Peoples’ Rights and Dignity: safeguard individual rights; protect rights of privacy and confidentiality

good, honest, just, respectful, responsible (GHJRR)

how many sections of ethical guidelines are there?

10

five specific points from Section 8 of the code of ethical guidelines

Standard 8: Research and Publication:
- Identify potential risks
- Protect participants from physical and psychological harm
- Justify remaining risks
- Obtain informed consent
- Take care of participants after the study (debriefing)

What is the IRB and what does it do?

Institutional Review Board: determines whether the project meets ethical guidelines
Key factor: degree of risk to subjects No risk (could be exempt) Minimal risk (expedited) At risk (full)

Issues with IRBs

Issues: judging methodological adequacy, no appeal, anti-basic research, overly cautious

what are some important elements of consent?

- Study’s basic description
- Enough information to decide whether to participate
- How long participation will take
- May quit at any time
- Confidentiality and anonymity ensured
- Contact information given (researcher, IRB)
- Opportunity to obtain final results of the study
- Signatures

plagiarism

the presentation, with intent to deceive, or with disregard for proper scholarly procedures of a significant scope, of any information, ideas or phrasing of another as if they were one’s own without giving appropriate credit to the original source

falsifying data

Range from individual weakness to societal moral standards (sometimes due to the publish or perish climate in academia)

basic vs applied research

Basic: designed to understand fundamental psychological phenomena ex → stimulus factors affecting selective attention
- Describing, Predicting, Explaining

Applied: designed to shed light on the solution to real-world problems ex → effect of cell phone use on driving
- Solving real-world problems, Education, Poverty, Risky behavior, Job performance (training)

laboratory vs field research

Lab
- Focus on the independent variable
- Measure the dependent variable
- Controlling extraneous variables
- More scientific
- But is artificial

Field
- More realistic
- Real-world validity
- Issues of ethics and privacy
- Participants may self-select

Quantitative vs Qualitative research

Quantitative
- Data collection
- More “scientific”

Qualitative
- Anecdotal
- Focus groups
- Opinion
- More “rich” and human

operational definitions

A strict and valid operational definition will add clarity and definition to research

Should be logical, understandable, observable, and measurable

developing research from serendipity

Serendipity: real-world events spark experimental designs

developing research from theory

Theory: Summarizes, organizes, explains, provides basis for predictions. Includes constructs → hypothetical factors involved in the attempt at explanation e.g., cognitive dissonance
- Hypotheses deduced from theory
- Outcomes/data provide or fail to provide inductive support for theory theories are never “true” nor “false”

developing research from other research

Replication:
Direct replication: a reproduction of the exact study procedures as the original study
Conceptual replication: a partial replication, with new features added to extend the original study’s finding

four attributes of good theories

- They should advance knowledge
- They should be subject to falsification
- They should be Parsimonious (minimum number of constructs and assumptions)
- They should solve real-world problems

SPAF (solve, parsimonious, advance, falsification)

inductive vs deductive reasoning

Inductive Reasoning
- Going from the specific to the general.
– An inductive generalization.

Deductive Reasoning
– Going from the general to the specific.
– A deductive argument (a proof).

explain Mill’s Inductive logic

Method of agreement: If X, then Y (sufficiency → X is sufficient for Y)

Method of difference: If not X, then not Y (necessity → X is necessary for Y)

Together → X is necessary & sufficient for producing Y

agreement and difference in inductive logic

Agreement – analogous to experimental group
Difference – analogous to control group

conditional statements

If (antecedent) then (consequent) or (Consequent) if (antecedent).

A conditional statement is not in itself an argument, but it may serve as either the premise or conclusion (or both) of an argument.

what is Modus Ponens

the way that affirms by affirming

valid form of Modus Ponens

1a. Modus Ponens (affirming the antecedent: valid)
If P, then Q.
P.
Therefore Q

invalid form of Modus Ponens

1b. Invalid Form of Modus Ponens (the logical fallacy of affirming the consequent)
If P, then Q.
Q.
Therefore P.

what is modus tollens

the way that denies by denying

valid form of modus tollens

2a. Modus Tollens (denying the consequent: valid)
If P, then Q.
- Q.
Therefore – P

invalid form of modus tollens

2b. Invalid Form of Modus Tollens (the logical fallacy of denying the antecedent)
If P, then Q.
-P.
Therefore, -Q.

draw the chart of conditional statements

secondary reinforcer

something that leads to reinforcement or can be exchanged for a reinforcer i.e. money or gambling chips.

discriminative stimulus

an environmental stimuli that signals potential changes in the relationship between the response and the consequence.

chaining

a sequence of secondary reinforcers or discriminative stimuli.

spontaneous recovery

the behavior was extinct but is emitted again after a time delay.

draw the chart of reinforcement training

fixed ratio vs variable ratio

Fixed Ratio: i.e. 1:1, 2:1, etc.
- 2:1 means press bar twice for 1 pellet

Variable Ratio: i.e. average (mean) of 2:1, 5:1, 10:1, etc. (emails, approval, gambling)
- the number of bar presses varies but stays around the mean of a set ratio (4:1; 6:1; 5:1; 6:1; 4:1)

fixed interval vs variable interval

Fixed Interval: i.e. each 30 seconds if there has been an appropriate response during the time interval.
- no matter how many times the rat presses the bar during 30 seconds, he gets one pellet
- if he does not press the bar in 30 seconds, he gets no pellet

Variable Interval: i.e. average (mean) of 30 seconds…

extinction

the response is extinguished, and the behavior becomes extinct. Which last longer?
- the rat no longer presses the bar

name and explain three different types of probablility sampling

Random sampling
- Each member of pop. has equal chance of being selected as member of sample
- Sometimes use a random number generator to select from population

Stratified sampling
- Proportions of important subgroups in pop. are represented precisely in sample
- 75% female; 25% male (2 strata)

Cluster sampling
- randomly select a cluster of individuals all having some feature in common
- campus survey → sample first-year students who live on-campus

name and explain three types of nonprobablilty sampling

Convenience sampling
- Select subjects who are available and convenient (e.g., Introductory Psychology “subject pool”)
- Purposive sampling (e.g., Milgram non-use of university students)

Quota sampling
- Similar to stratified sampling, but non-random

Snowball sampling
- Ask subjects to get their acquaintances to participate
- Often done with online surveys

reliability vs validity

Reliability
- Is it repeatable?
- Does it give us (almost) the same result each time
- What is the measurement error?
- Reliability = repeatability, consistency

Validity
- Does it measure what it is designed to measure?

three types of validity

Face Validity: Does it appear on the surface to be valid?

Criterion Validity: Does it accurately forecast future behavior? (predictive); Is it a useful measure of behavior?

Construct Validity: Is the construct being measured a valid construct? Is this the best instrument for measuring it?

four scales of measurement

Nominal → Categories

Ordinal → Categories with a true order

Interval → Equal fixed intervals between items but no true zero. You can add but not divide.

Ratio → A true zero. You can divide or multiply.

how are nominal scales used and provide an example

assign numbers to events to classify them into one group or another; numbers are used as names [categorical]

How used:
- assign individuals to categories
- count the number of individuals falling into each category (reported as frequencies)

Example:
Verdict: 0 = not guilty, 1 = guilty
Sparrow, robin, owl, eagle, wren

how are interval scales used and provide an example

scores indicate quantities; equal intervals between scores
- score of zero → just a point on the continuum and does not indicate ‘absence’ of something

How used: calculate score from participants’ responses on a test

Examples: temperature, IQ scores, scores from personality tests

how are ratio scales used and privde an example

with ratio scales we can add, subtract, multiply, divide and a ratio scale has a true zero.

How used: number of people testing (doubled by half; cut by half)

Example
- The number of people are enrolled in this class.
- The amount of money in an account.
- The number of people who test positive for a disease

descriptive vs inferential statistics

Descriptive Statistics: summarize and provide measurements about a sample or population data

Inferential Statistics: permit us to draw inferences (generalizations) from what we have observed and measured.

explain NHST

Null Hypothesis Significance Testing (NHST)

Null Hypothesis: No relationship (“no difference”) between variables in the population expected, given our sample (H0)

Alternative Hypothesis: A relationship (a difference) between variables in population is expected, given our sample

A researcher’s predictions often specifies the direction of the relationship (e.g., a positive correlation between variables)

what are the two possible outcomes for null hypothesis significance testing

Reject null hypothesis (with some probability)
- Conclude you found a significant relationship between variables

Fail to reject the null hypothesis
- Conclude you found no significant relationship between variables

what are the errors in NHST

Possible Errors:

Type I → reject null hypothesis, but be wrong (false positive)

Type II → fail to reject null hypothesis, but be wrong (false negative)

draw the NHST table

explain four different types of variables

Independent: We manipulate (sort of or usually) the IV.
- Situational: Manipulation of different features in the environment that may occur.
- Task: Different tasks, different levels of complexity, different scenarios.
- Instructional: Manipulated by asking groups to perform in different ways

Dependent: We measure the DV.

Extraneous or Confounding: We control these.

Subject (participant): Who the person is as they come to the experiment:
- Male vs famale
- Age groups
- Educational levels
- Diagnosed vs healthy

what are extraneous variables

Uncontrolled factors that are not of interest but might influence the behavior being studied.

external vs internal validity

External Validity: Can our inferences from this sample be generalized to other populations? other settings? other groups? other times? other cultures?

Internal Validity: Does my study actually answer the research question I proposed and designed to answer?

what are the three needs for validity?

have valid operational definitions.

have valid measurements.

have no confounds.

history vs maturation

History: Events occur, things change, the effects of the Parkland, Florida shootings

Maturation: Did 5th grade make you smarter or was it a year of maturation?

what are the 10 steps in scientific research

1. form a question
2. form a hypothesis
3. operationalize the question
4. determine your sample
5. run the experiment and make observations
6. record data
7. analyze the data using statistics
8. make inferences based on data analysis
9. form conclusions and answer the original question
10. build conclusions into a theory

QHOSEDAICT (more than just PI HED C)

what are the two objectives of writing a research report

Science: To move science forward
- To share with colleagues
- To collectively seek truth

Selfish: To get published and funded
- To enhance your stature as a scientist
- To enhance your own career

what are the sections of an APA paper

Title Page
Abstract
Introduction
Method
Results
Discussion
Conclusion

TAIMRDC

should results only include significant differences?

We should NOT present only significant differences?
- if there is no statistically significant difference, then report that!!
- if there is no difference (men/women) and you want to eliminate something as a possible explanation?

how to write significant and marginally significant

Don’t write “significant results.” They are “significant differences.”

Never write “insignificant” → write “statistically non-significant”

explain what between-subjects design is and provide an example from the coffee experiment

A comparison of measures of the DV between different participants.
- Each participant experiences one* IV and produces one measurement on the DV.

Example: We give participants from one group caffeinated coffee (the IV), and participants from the other group decaffeinated, and we compare average scores for each group on a memory task (DV).

when is a between subject design essential?

Essential if the IV is a subject variable → need for equivalent groups

what is the main issue for a between subjects design and how do we try to solve it?

Main problem to solve → creating equivalent groups
- random assignment
- matching

what is random assignment

- Each subject has equal chance of being assigned to any group in the study
- Spreads potential confounds equally through all groups
- Blocked random assignment: involves assigning a subject to each condition of the study before the condition is repeated

what is matching and when is it used

Deliberate control over a potential confound

Use when:
- Small n per group might foil random assignment
- Some matching variable correlates with DV
- Measuring the matching variable is feasible

when is different sets of subjects in the IV necessary

Subjects in each condition have to be naïve (haven’t experienced the test before)

Subject variable (e.g., gender) is the IV

explain what within-subjects design is and provide an example from the coffee experiment

A comparison of measures of the DV within each participant (repeated-measures designs)
- Each participant experiences all (two or more) IVs and produces measurements for each on the DV.

Example: We give all participants caffeinated coffee (IV) and score them on a memory task (DV). After a few days, we give them all decaffeinated and score them on a memory task. We then compare DV scores within each participant.

when is a within subject design essential?

Used when comparisons within the same individual are essential (e.g., perception studies)

Eliminates the possibility that differences between levels of the DV could be due to differences between individual participants because it’s the same person

what is the main issue for a within subjects design and how do we try to solve it?

Main problem to solve → order effects
- Sequence Effects – controlled by random order
- Progressive Effects – also controlled by random order; the effect is the same from trial to trial
- Carryover effect – when one sequence may produce results different rom another sequence - Performance on or experience in Sequence A-B may affect performance (i.e., ‘carry-over’) on Sequence B-A

how do we control for order/sequencing effects?

Counterbalancing:
- Altering the order of the experimental conditions

Testing once per condition:
- Complete Counterbalancing (n!) ABC ACB BAC BCA CAB CBA - Partial Counterbalancing (when n! is too large)

Testing more than once per condition:
- Reverse Counterbalancing ABCD DCBA
- Block Randomization (all once before any repeats)

three types of designs in developmental research and issues with their use

Cross-sectional design: Comparing different age groups now
- Potential for cohort effects and worse with large age differences
- between subjects

Longitudinal design: comparing different people across time
- Potential for attrition difficulties
- Within-subjects design

Cohort sequential design: Combines cross-sectional and longitudinal

explain experimenter bias and how we control for it

Experimenter expectations can influence subject behavior

Blind and…Double blind
- blind - subjects don’t know
- double blind - subjects and experimenters don’t know
automates the procedure

what is the participant bias and how do we control for it

Hawthorne effect: effect of knowing one is in a study
“Good” subjects: participants tend to be cooperative, to please the researcher
Evaluation apprehension: participants tend to behave in ideal ways so as not to be evaluated negatively

Controlling for Participant Bias
- Effective deception
- Use of manipulation checks
- Field research

five ethical responsibilities for participants

Be responsible - Show up for scheduled appointments, or inform research of cancellation

Be cooperative - Behave professionally when participating in research

Listen carefully - Ask questions if unsure of your rights or of what you are asked to do

Respect the researcher - Do not discuss study with others

Be actively involved in debriefing - Help the researcher understand your experience

what is a hit

When there actually is a signal and the intensity of the signal is above the Detection Threshold, the signal will be perceived.

what is a correct nondetection

When there actually is no signal – only background noise – and the intensity is below the Detection Threshold, there will be no perception of a signal.

what is a miss

When there actually is a signal but the intensity of the signal is below the Detection Threshold, the signal will not be perceived.

what is a false alarm

When there actually is no signal – only background noise – but the intensity is above the Detection Threshold, there will be a false perception of a signal.

which two responses are correct and which two are incorrect in signal response theory?

correct: hit and correct nondetection

incorrect: miss and false alarm

where do we place the threshold if there is a space between the Noise Curve and the Signal Plus Noise Curve?

place the threshold between them and get only Hits and Correct Nondetections

what happens if we raise a threshold?

We will get more misses and CNDs

We will get fewer hits or false alarms.

what happens if we lower a threshold?

We will get more hits and false alarms

We will get fewer misses and CNDs.

draw and label the signal detection theory

explain signal detection theory in terms of the NHST chart

Null is True and Fail to Reject Null Hypothesis → Correct Decision → Correct NonDetection

Null is True and Reject Null Hypothesis → Type 1 Error → False Alarm

Null is False and Fail to Reject Null Hypothesis → Type 2 Error → Miss

Null is False and Reject Null Hypotheses → Correct Decision → Hit