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1. Chapter 14
Quantitative Data Analysis
 Quantification of data
 Univariate Analysis
 Subgroup Comparisons
 Bivariate Analysis
 Introduction to Multivariate Analysis

2. Developing Code Categories
Two basic approaches:
 Beginning with a coding scheme derived from
the research purpose.
 Generate codes from the data.

3. Codebook Construction
Purposes:
 Primary guide used in the coding process.
 Guide for locating variables and interpreting
codes in the data file during analysis.

4. Entering Data
 Data entry specialists enter the data into an
SPSS data matrix or Excel spreadsheet.
 Optical scan sheets.
 Part of the process of data collection.

5. Quantitative Analysis
 Univariate - simplest form,describe a case in
terms of a single variable.
 Bivariate - subgroup comparisons, describe a
case in terms of two variables simultaneously.
 Multivariate - analysis of two or more variables
simultaneously.

6. Univariate Analysis
 Describing a case in terms of the distribution of
attributes that comprise it.
Example:
 Gender - number of women, number of men.

7. Presenting Univariate Data
Goals:
 Provide reader with the fullest degree of detail
regarding the data.
 Present data in a manageable from.

8. Subgroup Comparisons
 Describe subsets of cases, subjects or
respondents.
Examples
 "Collapsing" response categories.
 Handling "don't knows."

9. Bivariate Analysis
 Describe a case in terms of two variables
simultaneously.
 Example:
– Gender
– Attitudes toward equality for men and women

10. Constructing Bivariate Tables
 Divide cases into groups according to the
attributes of the independent variable.
 Describe each subgroup in terms of attributes
of the dependent variable.
 Read the table by comparing the independent
variable subgroups in terms of a given attribute
of the dependent variable.

11. Multivariate Analysis
 Analysis of more than two variables
simultaneously.
 Can be used to understand the relationship
between two variables more fully.