Sociology 690 data analysis
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Sociology 690 – Data Analysis. Simple Non-Quantitative Data Analysis. Grouping Non-Quantitative Data. Frequencies Percentages Ratios Rates. Graphing Non-Quantitative Data. Pie Charts and Bar Graphs 3-D Graphs Pictographs Population Pyramids. Cross-classifying NQ Data.

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Sociology 690 – Data Analysis

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Sociology 690 data analysis

Sociology 690 – Data Analysis

Simple Non-Quantitative

Data Analysis


Grouping non quantitative data

Grouping Non-Quantitative Data

  • Frequencies

  • Percentages

  • Ratios

  • Rates


Graphing non quantitative data

Graphing Non-Quantitative Data

  • Pie Charts and Bar Graphs

  • 3-D Graphs

  • Pictographs

  • Population Pyramids


Cross classifying nq data

Cross-classifying NQ Data

  • Column, Row and Cell Marginals

  • Percentaging Tables

  • Simple Summary Statistics

    • Lambda

    • Gamma

    • Chi Square


Sociology 690 data analysis

The Non-Quantitative Elaboration Model

A. Elimination

B. Specification

Spuriousness

X

e.g. the effectof fire size (Z) on the relationship between # of firemen (X) and damage (Y)

1. Antecedent

Z

Y

2. Intervening

X

Y

e.g. the effectof education (Z) on the relationship between age (X) and income (Y)

Z


Sociology 690 data analysis

Non-quantitative Statistical Example

Step 1 – Construct the zero order cross-tabulation table.

The Marginal (Zero-Order) Table

Step 2 – Calculate the zero order measure of association.

e.g. Lambda = 40/40 – 30/40 = .25


Sociology 690 data analysis

Step 3 – Construct the first order partial tables.

The Marginal Table

Partial Table for Young

Partial Table for Old

=

+

Step 4 – Calculate the partial measures of association

TotalYoungOld

Lambda .25 .001.00

Step 5 – Form the conclusion

Since the partials have changed from the marginal measure, one getting stronger and the other disappearing, we would say that we have specified the zero order relationship as probably intervening (i.e. we are born into a sex, grow older and as a result, join a political party).


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