Chapter 2 Flashcards
Population
The entire group to which a law of nature applies
Sample
A subset of a population intended to represent the population
Representative sample
Accurately represents the characteristics and behaviors of individuals in the population
Random sampling
Selecting a sample which each member of a population has an equal chance of being selected
Hypothetical construct
An abstract concept used to summarize and describe behaviors that share certain attributes
Contracts are intentionally general why?
So that they may be examined from many different perspectives
Variable
Any measurable aspect of a behavior or influence on a behavior that may change
How do we examine an aspect of a hypothetical construct?
By selecting a specific variable to measure
Quantitative variable
The score indicates the amount of the variable
Qualitative variable
Indicates a quality or category
Operational definition
Defines a variable by the specific operations used to measure it
How is each variable in the study defined?
In the terms of the procedure used to measure it
Relationship
When a change in one variable is accompanied by a consistent change in another variable
Strength of a relationship
The extent to which one value of Y is consistently associated with one value of X
Two reasons relationships are not perfectly consistent
External influences and individual differences
Individual differences
No two individuals are identical, which may influence behavior in any given situation
In research, what parts of the relationship are we concerned with?
The strength and existence.
What is the given variable?
X
What is the other variable?
Y
The scores on Y change as a what to X?
A function
Data point
Dot on a graph
Descriptive statistics
Procedures for organizing and summarizing scores so that we can describe and communicate the important characteristics of the data
Purposes of Descriptive statistics
Tell if there is a relationship, summarize scores and describe the data, and predict behavior
Inferential statistics
To infer the description applicable to everyone in the population based on the sample data; Procedures for deciding if the sample data represents the population. If the sample is believable
Does a sample always accurately represent a population?
No
Generalize
Apply conclusions to other individuals or situations
Two ways we generalize
The relationship in the sample to the population, and variables in the population to the relationship between broader hypothetical constructs
Experiment
Actively changes or manipulates one variable and measures the resulting behavior
Independent variable
Directly changed
Confederates
People enlisted to act as other participant or accidental passerby’s
Condition/level/treatment
A specific amount or category of the independent variable that the researcher selects to create the situation under which the participants are observed
Independent variable:Conditions
Entire causal variable of interest: specific amounts/ categories of the variable
Control group
Measured for the dependent variable but receives no independent variable or treatment
Experimental group
Receives a nonzero amount of the independent variable
True experiment
The independent variable is controlled by the researcher
True independent variable
Controlled by the researcher
Random assignment
Condition of independent variable is determined by chance
Quasi-independent variable
Variables which cannot be manipulated
Quasi-experiment
Not what the researcher does to the participant, but the participant is assigned to a particular condition because ethic already qualify for it
Dependent variable
Reflects some aspect of the participants or their behavior
Reaction time
Amount of time the participant takes to respond
Forced-choice procedure
Participants select form a limited set of choices
Sorting task
Indicate similarities or differences by sorting the stimuli into different groups
Self-reports
Asked to describe their feelings, beliefs, or attitudes
Likert-type questions
Rate a series of statements
Intervening variables
Influenced by the independent variable, which in turn influences the dependent variable
Descriptive design
Simply observe behaviors or relationships so that we may describe them
Correlation design
Passively measure scores on at least two variable and determine whether the scores form the predicted relationship
