Beyond Statistics: A Practical Guide to Data Analysis / Edition 1

Beyond Statistics: A Practical Guide to Data Analysis / Edition 1

by Benjamin O. Miller
     
 

ISBN-10: 0205317448

ISBN-13: 9780205317448

Pub. Date: 10/23/2000

Publisher: Allyn & Bacon, Inc.

A practical introduction to terms, concepts, and processes of data analysis, introducing operations common to all statistical software. This book goes beyond basic research methods and statistics, and discusses actually working with data, including data entry, data cleaning, finding errors, organizing data, transforming variables, and combining and aggregating data

Overview

A practical introduction to terms, concepts, and processes of data analysis, introducing operations common to all statistical software. This book goes beyond basic research methods and statistics, and discusses actually working with data, including data entry, data cleaning, finding errors, organizing data, transforming variables, and combining and aggregating data sets. It provides a useful vocabulary for thinking and talking about data and demystifies statistical software by showing readers how to think about data from the computer's perspective. People with an interest in research methods, experimental methodology, and statistics in the fields of psychology, sociology, and social work.

Product Details

ISBN-13:
9780205317448
Publisher:
Allyn & Bacon, Inc.
Publication date:
10/23/2000
Pages:
181
Product dimensions:
8.50(w) x 10.98(h) x (d)

Related Subjects

Table of Contents

Preface vi
Orientation
1(10)
Variables, values, and constants
2(1)
Kinds of variables
2(2)
Independent and dependent variables
2(1)
Discrete and continuous variables
3(1)
Categorical and quantitative variables
3(1)
Kinds of questions
4(4)
Questions about a distribution
4(2)
Questions about differences
6(1)
Questions about associations
7(1)
Questions about relations
7(1)
Some principles of data analysis
8(3)
Have a destination
8(1)
Look at the data
8(1)
Avoid unnatural acts with data
9(2)
The tools of data analysis
11(6)
Computing and data storage
11(2)
Software
13(3)
Input processes
13(1)
Data editor
13(1)
User interface
13(2)
Data manipulation tools
15(1)
Statistical computation tools
15(1)
Graphing tools
15(1)
Output operations
15(1)
What doesn't statistical software do?
16(1)
Data in the computer
17(22)
Data files
17(3)
Data storage types
20(1)
Strings
21(1)
Encoding strings
22(1)
Value labels
23(1)
Missing values
24(4)
Getting data into the computer
28(2)
Native files
28(1)
Text files
28(1)
Non-native files
29(1)
From scratch
29(1)
Make a text file
29(1)
Use the data editor
29(1)
Set up a database
29(1)
Code books and data dictionaries
30(3)
Exercises
33(6)
Looking at Faces, Part I
35(4)
Data structures and operations
39(20)
Casewise and scorewise structures
40(2)
Using casewise and scorewise data
42(2)
Software limitations
44(2)
Mixed structures
46(1)
Changing structure
47(7)
Being selective
54(2)
Exercises
56(3)
Checking Data
59(18)
Brute force methods
59(2)
Intelligent methods
61(7)
Improbable values
61(2)
Impossible values
63(1)
Out-of-range value
63(1)
Wrong value type
64(2)
Impossibly missing value
66(1)
Inconsistent values
66(2)
Exercises
68(9)
Looking at Faces, Part II
70(7)
Transforming Data
77(20)
Encoding string variables
78(3)
Making continuous variables discrete
81(1)
Arithmetic operations on one or more variables
82(1)
Exercises
83(1)
Practice Analysis: Who uses gloves
84(1)
Practice Analysis: Evaluating reading instruction methods
85(12)
Comparing the nutritional content of breakfast cereals
87(5)
Effect of expectation on binocular fusion
92(5)
Combining data sets
97(28)
Appending data
97(2)
One-to-one merges
99(1)
Match merges
100(4)
Summary
104(1)
Exercises
105(20)
GNP and Life Expectancy
107(8)
Popularity and Priorities
115(5)
Cutting it Close
120(5)
Displaying data in tables
125(8)
Frequency tables
125(3)
Summary tables
128(2)
Exercises
130(3)
Displaying data in graphs
133(10)
Histograms
133(1)
Bar graphs
134(2)
The box-and-whisker plot
136(1)
The line graph
137(3)
The scatter plot
140(2)
Exercises
142(1)
Collapsing data sets
143(24)
The simplest case
145(1)
Adding a second summary measure
146(1)
Adding a second independent variable
147(1)
Adding a second dependent variable
148(2)
Exercises
150(17)
Looking at Faces, Part III
152(9)
Sundown Syndrome
161(6)
Appendix A: Popular Software Equivalents of Pseudocode Commands 167(4)
Appendix B: Descriptions of Data Files 171(7)
References 178(1)
Index 179

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