Data analysis with spreadsheets
著者
書誌事項
Data analysis with spreadsheets
Pearson/Allyn & Bacon, c2006
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注記
Includes bibliographical references (p. 187-193)
内容説明・目次
内容説明
David A. Patterson and Randall E. Basham have produced the first book and CD-ROM to combine text, video and graphs to clearly describe and illustrate how social workers can use spreadsheets to collect data, analyze statistics and create graphs of research results. Students and professionals will find this an excellent guide to taking advantage of spreadsheet software, an underutilized, inexpensive and commonly available data analytic tool found in most, if not all, agency settings.
Data Analysis with Spreadsheest offer instructors clearly articulated descriptions and video demonstrations of data analysis procedures that are commonly referred to in research and practice evaluation texts. This text and CD-ROM present a variety of ways to select random samples and clearly demonstrate how to produce descriptive statistics, frequency distributions, and bivariate analyses using spreadsheets.
目次
Each chapter concludes with "Chapter Summary" and "References."
1. An Introduction to Spreadsheets.
Spreadsheets - First Facts.
The Brief History of Spreadsheets.
Why Use Spreadsheets for Data Analysis in the Social Services?
Spreadsheet Basics.
Using Formulas and Functions.
Advanced Tools for Understanding Data.
A Comparison of Spreadsheets to Statistical Analysis Software.
The Paradox of Spreadsheets and Statistical Software in Social Service Practice.
2. Data Collections Waysand Means.
The Many Paths to Data Acquisition.
Levels of Measurement.
Data Coding.
Basic Data Entry.
Creating Data Entry Forms.
Downloading Data.
Web-Based Data Retrieval.
Relating to Database Software.
Web-based Data Collection.
Relating to Database Software.
Saving What You Have and Using What You Need.
3. Selecting Samples.
Samples: First Facts.
Simple Random Samples.
Systematic Sampling.
Stratified Sampling.
Random Assignment.
4. Data Cleaning
Types of Problem Data.
Detecting Data Errors.
Contingency Cleaning.
Missing Data: Its Detection and Handling.
Detecting Missing Data.
Handling Missing Data.
5. Frequency Distributions and Histograms.
Understanding the Distribution of Values.
Frequency Distributions.
Producing Histograms Using the Chart Wizard.
6. Descriptive Statistics.
Measures of Central Tendency.
Formulas for Measures of Central Tendency.
Measures of Dispersion or Variability.
Data Analysis Tools: Descriptive Statistics.
Producing Frequency Polygrams.
7. Statistical Inference and Hypothesis Testing.
Normal Distributions.
Probability Distributions.
Skewness.
Understanding Hypothesis Testing.
Statistical Significance.
Effect Size and Sample Size Estimation.
8. Bivariate Statistics.
Chi-square Test of Independence.
t-Test.
ANOVA.
Post hoc Tests of Means.
9. Cross-Tabulation Tables.
Using the Pivot Tables Wizard.
Graphing Cross-tabulation Tables.
10. Single System Design.
Basic Elements of Single System Design.
Advanced Designs.
Dynamic Chart Production.
Single System Group Designs.
11. Correlation and Regeression.
Pearson's r and R2.
Bivariate Regressions.
Regression.
Two Variable Regression.
Creating Scatterplots.
Trendlines in Scatterplots.
Interpreting Scatterplots.
Ordinary Least Squares (OLS) Regression.
Interpreting Multivariate Regression (OLS) Output in Excel.
Creating a Control Variable for Regression Analysis in Excel.
12. Graphical Representation of Practice Information.
Thinking Visually.
Graphical Representation.
Tools for Graphical Representation of Information.
Matching Data to Type of Graph.
Enhancing Graphs.
Spreadsheets Drawing Tools.
Ecomaps.
Genograms.
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