16.05.2013 Views

Understanding Statistics in the Behavioral Sciences ... - NelsonBrain

Understanding Statistics in the Behavioral Sciences ... - NelsonBrain

Understanding Statistics in the Behavioral Sciences ... - NelsonBrain

SHOW MORE
SHOW LESS

You also want an ePaper? Increase the reach of your titles

YUMPU automatically turns print PDFs into web optimized ePapers that Google loves.

Licensed to:<br />

■ SUMMARY<br />

In this chapter, I have discussed how truth is established.<br />

Traditionally, four methods have been used: authority,<br />

reason, <strong>in</strong>tuition, and science. At <strong>the</strong> heart of science is<br />

<strong>the</strong> scientifi c experiment. By reason<strong>in</strong>g or through <strong>in</strong>tuition,<br />

<strong>the</strong> scientist forms a hypo<strong>the</strong>sis about some feature<br />

of reality. He or she designs an experiment to objectively<br />

test <strong>the</strong> hypo<strong>the</strong>sis. The data from <strong>the</strong> experiment are<br />

<strong>the</strong>n analyzed statistically, and <strong>the</strong> hypo<strong>the</strong>sis is ei<strong>the</strong>r<br />

confi rmed or rejected.<br />

Most scientifi c research falls <strong>in</strong>to two categories:<br />

observational studies and true experiments. Natural observation,<br />

parameter estimation, and correlational studies<br />

are <strong>in</strong>cluded with<strong>in</strong> <strong>the</strong> observational category. Their major<br />

goal is to give an accurate description of <strong>the</strong> situation,<br />

estimate population parameters, or determ<strong>in</strong>e whe<strong>the</strong>r<br />

two or more of <strong>the</strong> variables are related. S<strong>in</strong>ce <strong>the</strong>re is<br />

no systematic manipulation of any variable by <strong>the</strong> experimenter<br />

when do<strong>in</strong>g an observational study, this type of<br />

■ IMPORTANT NEW TERMS<br />

Constant (p. 6)<br />

Correlational studies (p. 9)<br />

Data (p. 7)<br />

Dependent variable (p. 7)<br />

Descriptive statistics (p. 10)<br />

Independent variable (p. 6)<br />

Inferential statistics (p. 10)<br />

Method of authority (p. 4)<br />

Method of <strong>in</strong>tuition (p. 5)<br />

Method of rationalism (p. 4)<br />

Naturalistic observation<br />

research (p. 9)<br />

Observational studies (p. 9)<br />

Parameter (p. 7)<br />

Parameter estimation research (p. 9)<br />

Population (p. 6)<br />

Important New Terms 17<br />

research cannot determ<strong>in</strong>e whe<strong>the</strong>r changes <strong>in</strong> one variable<br />

will cause changes <strong>in</strong> ano<strong>the</strong>r variable. Causal relationships<br />

can be determ<strong>in</strong>ed only from true experiments.<br />

In true experiments, <strong>the</strong> <strong>in</strong>vestigator systematically<br />

manipulates <strong>the</strong> <strong>in</strong>dependent variable and observes its effect<br />

on one or more dependent variables. Due to practical<br />

considerations, data are collected on only a sample of<br />

subjects ra<strong>the</strong>r than on <strong>the</strong> whole population. It is important<br />

that <strong>the</strong> sample be a random sample. The obta<strong>in</strong>ed<br />

data are <strong>the</strong>n analyzed statistically.<br />

The statistical analysis may be descriptive or <strong>in</strong>ferential.<br />

If <strong>the</strong> analysis just describes or characterizes <strong>the</strong><br />

obta<strong>in</strong>ed data, we are <strong>in</strong> <strong>the</strong> doma<strong>in</strong> of descriptive statistics.<br />

If <strong>the</strong> analysis uses <strong>the</strong> obta<strong>in</strong>ed data to <strong>in</strong>fer to<br />

populations, we are <strong>in</strong> <strong>the</strong> doma<strong>in</strong> of <strong>in</strong>ferential statistics.<br />

<strong>Understand<strong>in</strong>g</strong> statistical analysis has important practical<br />

consequences <strong>in</strong> life.<br />

Sample (p. 6)<br />

Scientifi c method (p. 6)<br />

SPSS (p. 11)<br />

Statistic (p. 7)<br />

True experiment (p. 9)<br />

Variable (p. 6)<br />

Copyright 2011 Cengage Learn<strong>in</strong>g. All Rights Reserved. May not be copied, scanned, or duplicated, <strong>in</strong> whole or <strong>in</strong> part. Due to electronic rights, some third party content may be suppressed from <strong>the</strong> eBook and/or eChapter(s).<br />

Editorial review has deemed that any suppressed content does not materially affect <strong>the</strong> overall learn<strong>in</strong>g experience. Cengage Learn<strong>in</strong>g reserves <strong>the</strong> right to remove additional content at any time if subsequent rights restrictions require it.

Hooray! Your file is uploaded and ready to be published.

Saved successfully!

Ooh no, something went wrong!