Psych Stats Chapter 1

Population of interest

The larger group that a researcher is interested in studying.

Sample

The subset of the population that participates in the study. Researchers hope the sample is representative of the population so findings can be generalized.

Variable

A condition or characteristic that can have different values.

Independent variable (IV)

The variable that gets manipulated, or the "input." It is what the researcher wants to see cause a change.

Dependent variable (DV)

The variable that gets measured, or the "outcome." It is what the researcher is looking for an effect in.

How to identify the IV and DV

The IV is what the researcher changes or manipulates, while the DV is what the researcher measures as the outcome. Example: if studying whether crowding affects aggression, crowding is the IV and aggression is the DV.

Goal of manipulating the IV

The researcher wants the IV to be the only thing that is different between conditions, while everything else is held constant as much as possible.

Physical crowding study

Research question: "I want to examine how physical crowding affects aggression." IV = crowding. DV = aggression.

Drug treatment study

Research question: "I wonder which of 3 different drugs is best for treating anxiety." IV = drug type. DV = anxiety.

Task difficulty study

Research question: "Do people focus best when a task is hard, easy, or in between?" IV = task difficulty. DV = focus.

Operationalization

The process of defining the exact, concrete way a variable will be measured or manipulated. This is also expressed as giving the variable an operational definition.

Why variables must be operationalized

Researchers need to turn an abstract variable into a specific procedure that can actually be measured or manipulated.

How many ways can a variable be operationalized?

Variables can be operationalized in many different ways. The researcher decides which operationalization to use and must motivate that choice.

Operationalizing drug type

Drug type can be operationalized as a daily, individually calibrated dose of an SSRI, SNRI, benzodiazepine, or placebo.

Operationalizing anxiety

Anxiety can be operationalized as a participant's score on the Hamilton Anxiety Scale (HAMA), measured before and after the intervention.

Hamilton Anxiety Scale (HAMA)

The scale used in the presentation to measure anxiety. Anxiety is assessed using HAMA scores before and after the intervention.

Pre-intervention vs. post-intervention anxiety measurement

Anxiety is measured with the HAMA before the treatment intervention and again after the intervention, allowing the researcher to assess the outcome associated with treatment.

True experiment

In a true experiment, the researcher manipulates the independent variable.

What does it mean to manipulate the IV?

The researcher actively determines which condition or level of the independent variable participants experience.

Random assignment

Participants are randomly assigned to different experimental conditions. In the presentation's drug example, participants are randomly assigned to a drug condition upon diagnosis.

Why random assignment is used in the drug experiment

Random assignment determines which drug condition participants receive, rather than allowing preexisting differences between participants to determine their condition.

True experiment drug example

Participants are randomly assigned to receive one of the drug conditions, such as an SSRI, SNRI, benzodiazepine, or placebo. Because the researcher assigns the drug condition, drug type is manipulated.

Quasi-experiment or correlational study

A study in which the independent variable is not manipulated by the researcher. The presentation gives naturally occurring groups as an example.

Naturally occurring groups

Groups that already exist before the researcher's intervention or assignment. When researchers study these groups, the IV is not manipulated by the researcher.

Drug study using naturally occurring groups

Researchers recruit 100 participants who are already taking each drug type. Because the researchers did not assign participants to the drug conditions, drug type is not manipulated.

True experiment vs. quasi-experiment/correlational study

The key distinction presented is manipulation of the IV. In a true experiment, the researcher manipulates the IV. In a quasi-experiment or correlational study, the IV is not manipulated and may come from naturally occurring groups.

Researcher-assigned drug condition vs. existing drug use

If researchers randomly assign participants to drug conditions, the study is a true experiment. If they recruit people who are already taking different drugs, the drug groups are naturally occurring and the IV is not manipulated.

Manipulation vs. measurement

Manipulation refers to changing or assigning the independent variable. Measurement refers to recording the dependent variable.

Crowding and aggression: identify the variables

Crowding is the independent variable because it is the factor being manipulated or varied. Aggression is the dependent variable because it is the outcome being measured.

Drug type and anxiety: identify the variables

Drug type is the independent variable because it is the treatment condition being varied. Anxiety is the dependent variable because it is the outcome being measured.

Task difficulty and focus: identify the variables

Task difficulty is the independent variable because its level is varied. Focus is the dependent variable because it is the outcome being measured.

Example of an operationalized IV vs. DV

For the drug study, the IV "drug type" is operationalized as receiving a daily individually calibrated dose of an SSRI, SNRI, benzodiazepine, or placebo, while the DV "anxiety" is operationalized as a HAMA score measured before and after the intervention.

What must be specified for an abstract variable?

The researcher must specify the exact, concrete way the variable will be measured or manipulated. This specification is its operationalization.

Core logic connecting the concepts

Researchers begin with a population of interest and study a sample, identify variables, distinguish the IV from the DV, operationalize the variables, and, in a true experiment, manipulate the IV while measuring the DV.