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How to Manage, Analyze, and Interpret Survey Data
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How to Manage, Analyze, and Interpret Survey Data

Second Edition

October 2002 | 152 pages | SAGE Publications, Inc

"A useful and readable introduction to data analysis and valuable resource for the nonspecialist."

--Cameron Lee, Fuller Theological Seminary

Clearly written with useful checklists, guidelines, and examples, How to Manage, Analyze, and Interpret Survey Data shows readers how to manage survey data and become better users and consumers of statistical and qualitative survey information. Fink explains the basic vocabulary of data management and statistics, and then demonstrates the principles and logic behind the selection and interpretation of commonly used statistical and qualitative methods to analyze survey data: from cleaning the data to measurement scales through to how to read computer output and judge significance using confidence intervals. Thoroughly reorganized and revised, the book now includes coverage of:

* How to organize and manage data for analysis

* How to draft an analysis plan

* How to define and format a data file

* How to create a complete code book, including how to establish the reliability of the coding

* How to calculate the odds ratio and risk ratio

* How to do the basic steps in a content analysis of qualitative data

* How to recognize and deal with missing data and outliers for recoding

* How to enter data accurately into spreadsheets, database management programs, and statistical programs

"The author provides an excellent introductory overview to selecting appropriate statistical tests--the purposes and prerequisites for using various statistical methods."

--Kathy Sexton-Radek, Elmhurst College


 
How to Manage, Analyze, and Interpret Survey Data:
Learning Objectives
 
Ch 1. Data Management
Drafting an Analysis Plan

 
Creating a Codebook

 
Establishing Reliable Coding

 
Measuring Agreement Between Two Coders:
The Kappa Statistic

 
Reviewing Surveys for Missing Data

 
Entering the Data

 
Cleaning the Data

 
Some Surveys Have Not Been Returned

 
Some Returned Surveys Have Data Missing

 
Some People Are Outliers

 
Some Data Need to Be Recoded

 
 
Ch 2. What Statistics Do for Surveys
Measurement Scales: Nominal, Ordinal,
and Numerical

 
Nominal Scales

 
Ordinal Scales

 
Numerical (Interval and Ratio) Scales

 
Independent and Dependent Variables

 
Checklist for Choosing a Method to Analyze Survey
Data

 
Descriptive Statistics and Measures
of Central Tendency:
Numerical and Ordinal Data

 
Mean

 
Median

 
Mode

 
Distributions: Skewed and Symmetric

 
Checklist: When to Use the Mean, Median,
and Mode

 
Measures of Spread

 
Range

 
Standard Deviation

 
Percentile

 
Interquartile Range

 
Guidelines for Selecting Measures of Dispersion

 
Guidelines for Selecting Measures of Dispersion 000
Descriptive Statistics and Nominal Data

 
Proportion and Percentage

 
Ratio and Rate

 
 
Ch 3. Relationships and Comparisons
Numerical Data

 
Calculating the Correlation Coefficient

 
Size of the Correlation

 
Ordinal Data and Correlation

 
Regression

 
A Note on the Relationship Between Two Nominal
Characteristics

 
The Normal Distribution

 
Comparisons: Hypothesis Testing, p Values, and Confidence Levels
Confidence Levels

 
Guide to Hypothesis Testing,
Statistical Significance, and p Values

 
Risk and Odds

 
Odds Ratios and Relative Risk

 
 
Ch 4. Selecting Commonly Used Statistical Methods
for Surveys
Reading Computer Output

 
Chi-Square

 
t Test

 
Analysis of Variance (ANOVA)

 
Practical Significance: Using Confidence Intervals

 
Content Analysis of Qualitative Survey Data

 
Assemble the Data

 
Learn the Contents of the Data

 
Create a Codebook

 
Create a Codebook 000
Enter and Clean the Data

 
Do the Analysis

 
Relational Databases

 
Analysis of Open-Ended Questions: Best
and Least Liked

 
 
Exercises
 
Answers
 
Suggested Readings
 
Glossary
 
About the Author

"A useful and readable introduction to data analysis and valuable resource for the nonspecialist."

Cameron Lee
Fuller Theological Seminary

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