Chapter 2 - Psychological Research

Deductive reasoning

• results predicted based on a general premise or existing theory, typically quantitative

Inductive Reasoning

• conclusions are drawn from observations, typically qualitative 

Quantitative

• you can qualify or put a “value” on the information, numerical (ex: surveys)

Qualitative

• descriptive, describing a situation with words, not numbers, categorical (ex: interviews) 

Theory

• well-developed set of ideas that propose an explanation for observed phenomena

Hypothesis

•  a testable prediction about how the world will behave in your idea’s validity and is often worded as an “if-then” statement 

  • As specific hypotheses are tested, theories are modified and refined to reflect/incorporate test results

  • Hypothesis wording must be mutually exclusive and mutually exhaustive (both can’t happen at once)

Case study

• following one or a few participants; looking for details and rich information ( qualitative ) 

Naturalistic observation

• observing behavior in its natural setting while blending into the setting; looking for normal behavior, usually patterns, when people think they aren’t being watched, usually qualitative 

  • Ex: observing teenagers in a mall food court- not directly talking to individuals, but blending and listening to gather information 

Surveys

• lists of questions to be answered by research participants and can be delivered through questionnaires, verbally conducted, or electronically

  • Usually given to a sample of a population of people and also used to detect patterns, usually quantitative 

Archival research

• relies on looking at past records or data sets to look for interesting patterns or relationships

  • Typically data sets that are public records (publically available and free), such as sports statistics

Longitudinal research

• data gathering administered repeatedly over an extended period of time, typically looking to measure how things change over time or track a process 

• Attrition- over time, with each new trial, participants are lost (loss of interest, no longer applicable, etc) 

Attrition

• over time, with each new trial, participants are lost (loss of interest, no longer applicable, etc) 

Sample

• a smaller group of people within a larger group

Population

• larger group

  • Ex: this specific class is a sample of students taking PSYC101 (researchers can find samples in various ways) 

Correlation

• a statistical relationship between two or more variables 

Positive Correlation

• variables move in the same direction

  • Ex: time spent studying and grades, studying increases-grades also increase

Negative correlation

• variables move in opposite directions

  • Ex: time spent watching Stranger Things and grades, time watching Stranger Things increases- grades decrease

Correlation coefficients

• can span between -1.00 and +1.00 (closer to 0.00, the weaker the correlation) 

Perfect Correlations

• (-1.00 and +1.00)- impossible in the real world, perfect correlations often indicate faked data (unethical)

  • Correlation ≄ Causation (just because two things are correlated, doesn’t necessarily mean one causes the other) 

3 conditions

• Temporal Precedence- one thing has to happen to cause another 

• Establish a relationship- the two or more variables related, usually by correlation (cause related to effect)

• Rule out alternatives- confounding variables

  • Use logic (as a skeptic) to explain to someone your case. 

    • Ex: The amount of ice cream sold doesn’t necessarily cause the murder rate to increase, alternate reason

• Why (other condition)- can logically be explained why one variable causes another 

Temporal Precedence

• one thing has to happen to cause another 

Establish a relationship

• the two or more variables related, usually by correlation (cause related to effect)

Rule out alternatives

• confounding variables

  • Use logic (as a skeptic) to explain to someone your case. 

    • Ex: The amount of ice cream sold doesn’t necessarily cause the murder rate to increase, alternate reason

Experimental Design

• typically two groups in a standard experiment 

  • Experimental group- group that receives treatment 

  • Control group- group that doesn’t receive treatment but doesn’t know 

  • Operational definition- description of how you will measure your variables; important to allow others to understand what a researcher is measuring in an experiment 

Experimental group

• group that receives treatment 

Control group

•  group that doesn’t receive treatment but doesn’t know 

Operational definition

• description of how you will measure your variables; important to allow others to understand what a researcher is measuring in an experiment 

Single-blind Study

•  participants don’t know if they’re in the control group or the experimental groups (researchers know) 

Double-blind study

• neither participants nor researchers know who is in the control or experimental group 

Placebo effect

• when people’s expectations or beliefs influence or determine their experience in a given situation; not necessarily intentional lying

Independent variable

• what the researcher manipulates and changes throughout the experiment 

Dependent variable

• what the researcher measures to see how much effect the independent variable had 

  • Ex: (IV- sleep DV- test scores) researcher tests 3 students’ sleep the night before an exam, one of each pulls an all-nighter, gets 4 hours of sleep, and 8 hours.. the amount of sleep one gets determines the dependent variable 

Random sample

• a subset of a larger population in which every member of the population has an equal chance of being selected; best sampling method; all participants have an equal chance of being assigned to either group 

Report Findings in Peer-reviewed journals

• consists of writing up an article according to the specifications of a journal, submitting it, and waiting for other researchers to review your paper and either get back to you or accept the article (very rare), revising and resubmit or rejected (asking politely to publish elsewhere) 

  • Post-publication- once published, other researchers might want to replicate to be sure your findings aren’t just specific to your sample (ex: Freud’s very specific theory which was unsupported by many) 

    • Must explain exactly how the experiment was carried out so replication studies can be made similar to yours 

Post-publication

• once published, other researchers might want to replicate to be sure your findings aren’t just specific to your sample (ex: Freud’s very specific theory which was unsupported by many) 

  • Must explain exactly how the experiment was carried out so replication studies can be made similar to yours 

Reliability

• ability to do the same study more than once and arrive at the same (or similar) findings 

Validity

• accuracy of a given result in measuring what it is designed to measure 

Ethics

• consists of 3 important rules

  • Don’t make up data

  • Don’t fake results

  • Don’t lie

Institutional Review Board (IRB)

• approves every peer-reviewed journal publication

Informed Consent

• requires that researchers disclose information to the participant about a study before it begins and only involve participants if they agree to participate 

Subjects

• animals 

Participants

• humans  (are able to consent to a study) 

Institutional Animal Care and Use Committee (IACUC)

• - IRB for non-human studies (usually involving rats)