52 terms

# Statistics - the research process

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statistics
Set of mathematical procedures for organizing, summarizing and interpreting data
define constructs and variables and how they will be measured
The research process: 1) select research topic, 2) research question or hypothesis, 3) define the population and sample, 4) _____________, 5) design the study, 6) collect data, 7) analyze data, 8) draw conclusions, 9) share the findings (conference papers, publications).
collect data
The research process: 1) select research topic, 2) research question or hypothesis, 3) define the population and sample, 4) define constructs and variables and how they will be measured, 5) design the study, 6) _____________, 7) analyze data, 8) draw conclusions, 9) share the findings (conference papers, publications).
define the population and sample
The research process: 1) select research topic, 2) research question or hypothesis, 3) _____________, 4) define constructs and variables and how they will be measured, 5) design the study, 6) collect data, 7) analyze data, 8) draw conclusions, 9) share the findings (conference papers, publications).
3, 6, 9, 2, 7, 4, 1, 5, 8
Put the steps of the research process in order. 1) analyze data, 2) define constructs and variables and how they will be measured, 3) select research topic, 4) collect data, 5) draw conclusions, 6) research question or hypothesis, 7) design the study, 8) share the findings (conference papers, publications), 9) define the population and sample.
descriptive
Term for statistics used to summarize, organize and simplify data.
inferential
Term for statistics that use samples to make generalizations about the population.
sampling error
Term for the discrepancy between a sample statistic and corresponding population parameter.
variable
Term for a characteristic or condition that changes or has different values for different individuals.
data
Term for measurements of observations.
data set
Term for a collection of data.
score
Term for a single measurement.
constructs
Term for attributes or characteristics that cannot be directly observed (such as internal characteristics) but are useful for describing and explaining behavior (e.g. , intelligence, extraversion).
operational definition
Term for that which defines the construct in terms of behaviors that can be measured and observed (e.g., intelligence is performance on an IQ test).
nominal
Scale of measurement containing categories that have different names.
nominal
What type of scale of measurement would these examples have: gender, eye color?
nominal
What type of scale of measurement would these examples have: ethnicity, occupation?
ordinal
Scale of measurement containing categories organized in an ordering sequence.
ordinal
What type of scale of measurement would this example have: size of coffee at Starbucks?
ordinal
What type of scale of measurement would this example have: order of finish in a race?
interval
Scale of measurement containing ordered categories that are all intervals of exactly the same size.
interval
What type of scale of measurement would this example have IQ scores 100-110 110-120?
ratio
Scale of measurement containing an interval scale with an absolute zero point.
ratio
What type of scale of measurement would these examples have: time in seconds, weight in pounds?
correlational
Research method that investigates the relationship between variables by measuring two variables for each individual.
Experimental, non-experimental
Two research methods that investigate the relationship between variables by comparing two or more groups
measures at least two variables from each participant
The correlational research method involves: 1) ___________, 2) examines if there is a relationship between variables, 3) allows us to use one variable to "predict" the other, 4) cannot prove causality.
examines if there is a relationship between variables
The correlational research method involves: 1) measures at least two variables from each participant, 2) ___________, 3) allows us to use one variable to "predict" the other, 4) cannot prove causality.
allows us to use one variable to "predict" the other
The correlational research method involves: 1) measures at least two variables from each participant, 2) examines if there is a relationship between variables, 3) ___________, 4) cannot prove causality.
cannot prove causality
The correlational research method involves: 1) measures at least two variables from each participant, 2) examines if there is a relationship between variables, 3) allows us to use one variable to "predict" the other, 4) ___________.
predictor
Term used in correlational research method for the independent variable
criterion
Term used in correlational research method for the dependent variable
changes one variable to see if that causes changes in the second variable
The experimental research method involves: 1) __________, 2) rules out other explanations, 3) characterized by manipulation and control, 4) can prove cause-and-effect relationships.
rules out other explanations
The experimental research method involves: 1) changes one variable to see if that causes changes in the second variable, 2) __________, 3) characterized by manipulation and control, 4) can prove cause-and-effect relationships.
characterized by manipulation and control
The experimental research method involves: 1) changes one variable to see if that causes changes in the second variable, 2) rules out other explanations, 3) __________, 4) can prove cause-and-effect relationships.
can prove cause-and-effect relationships
The experimental research method involves: 1) changes one variable to see if that causes changes in the second variable, 2) rules out other explanations, 3) characterized by manipulation and control, 4) __________.
participant, environmental
Two types of confounding variables in experimental methods.
random assignment
Three techniques to control other variables: 1) _____________ , 2) matching (measure a variable and assign individuals to groups), 3) holding constant (e.g., participants are the same age).
Three techniques to control other variables: 1) random assignment, 2) _____________ , 3) holding constant (e.g., participants are the same age).
holding constant (e.g., participants are the same age)
Three techniques to control other variables: 1) random assignment, 2) matching (measure a variable and assign individuals to groups), 3) _____________ .
independent variable
The variable manipulated by the researcher.
dependent variable
What is observed in order to assess the effect of the treatment?
non-experimental
Research method that compares non-equivalent groups such as boys and girls
maximize benefit and minimize harm
General Ethical principles APA ethics code: 1) _____________, 2) fidelity and responsibility (trustworthy and accountable), 3) integrity (truthful, accurate, objective), 4) justice, 5) respect people's rights and dignity.
fidelity and responsibility (trustworthy and accountable)
General Ethical principles APA ethics code: 1) maximize benefit and minimize harm, 2) _____________, 3) integrity (truthful, accurate, objective), 4) justice, 5) respect people's rights and dignity.
integrity (truthful, accurate, objective)
General Ethical principles APA ethics code: 1) maximize benefit and minimize harm, 2) fidelity and responsibility (trustworthy and accountable), 3) _____________, 4) justice, 5) respect people's rights and dignity.
justice
General Ethical principles APA ethics code: 1) maximize benefit and minimize harm, 2) fidelity and responsibility (trustworthy and accountable), 3) integrity (truthful, accurate, objective), 4) _____________, 5) respect people's rights and dignity.
respect people's rights and dignity
General Ethical principles APA ethics code: 1) maximize benefit and minimize harm, 2) fidelity and responsibility (trustworthy and accountable), 3) integrity (truthful, accurate, objective), 4) justice, 5) _____________.
selectively using data
Examples of ethically bad use of data during data manipulation: 1) _________; 2) only using data that supports the hypothesis; 3) dropping data points; adn during data sharing: 4) refusing to share the data with other researchers.
only using data that supports the hypothesis
Examples of ethically bad use of data during data manipulation: 1) selectively using data; 2) _________ ; 3) dropping data points; and during data sharing: 4) refusing to share the data with other researchers.
dropping data points
Examples of ethically bad use of data during data manipulation: 1) selectively using data; 2) only using data that supports the hypothesis; 3) _________; and during data sharing: 4) refusing to share the data with other researchers.
refusing to share the data with other researchers
Examples of ethically bad use of data during data manipulation: 1) selectively using data; 2) only using data that supports the hypothesis; 3) dropping data points; and during data sharing: 4) _________.