Overview
- to
prepare completed surveys for data analysis
- to
analyze data using descriptive and inferential statistical tools.
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References: Chapters
15-18
Text
Concept Links
- editing
(p. 493)
- coding
(p. 499)
- data
entry (p. 502)
- one-way
tabulation (frequency distribution) (p. 511)
- cross
tabulation (p. 511)
- mean
(p. 533)
- mode
(p. 534)
- median
(p. 534)
- range
(p. 535)
- standard
deviation (p. 536)
- variance
(p. 536)
- hypothesis
testing (p. 537)
- t-test
(p. 541)
- analysis
of variance (ANOVA) (p. 543)
- f-test
(p. 545)
-
Chi-square analysis (p. 565)
- Pearson
correlation coefficient (p. 567)
- bivariate
regression analysis (p. 572)
- multiple
regression analysis (p. 578)
- multivariate
analysis (p. 598)
- factor
analysis (p. 601)
- cluster
analysis (p. 608)
- discriminant
analysis (p. 612)
- conjoint
analysis (p. 619)
- perceptual
mapping (p. 622)
Research Procedures
Step 1: Compile
all completed survey instruments.
Step 2:
Review and edit completed survey instruments for any errors
or to clarify responses.
Step
3: Enter
data to create files for processing. (Note: this process may
be performed manually for small sample studies.)
Step 4: Report appropriate descriptive data, such
as frequency distributions, mean scores, standard deviation,
and cross-tabulations.
Step 5: Use appropriate
inferential data analysis techniques, such as hypothesis test,
chi-square, t-test, ANOVA.
Weblinks
(click here)
Module output
Prepare a summary report consisting of the following components:
1.
A description of data analysis procedures.
2. A summary of descriptive and inferential data findings.
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