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) _________.

Example: