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9781590475768

Jmp For Basic Univariate And Multivariate Statistics: A Step-by-step Guide

by ; ; ;
  • ISBN13:

    9781590475768

  • ISBN10:

    1590475763

  • Format: Paperback
  • Copyright: 2005-03-31
  • Publisher: Sas Inst
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List Price: $69.95

Summary

Doing statistics in JMP has never been easier!Learn how to manage JMP data and perform the statistical analyses most commonly used in research in the social sciences and other fields with JMP for Basic Univariate and Multivariate Statistics: A Step-by-Step Guide. Clearly written instructions guide you through the basic concepts of research and data analysis, enabling you to easily perofrm statistical analyses and solve problems in real-world research. Step by step, you'll discover how to obtain descriptive and inferential statistics, summarize results, perform a wide range of JMP analyses, interpret the results, and more. Topics include: screening data for errors and selecting subsets with the JMP Distribution platform, computing the coefficient alpha reliability index (Cronbach's alpha) for a multiple-item scale, performing bivariate anlayses for all types of variables, performing a one-way analysis of variance (ANOVA), performing a multiple regression, and using the JMP Fit Model platform to perform a one-way multivariate analysis of variance (MANOVA). This user-friendly book introduces researchers and students of the social sciences to JMP and to elementary statistical procedures, while more advanced statistical procedures that are presented make it an invaluable reference guide for experienced researchers as well.

Table of Contents

Acknowledgments ix
Using This Book xi
Basic Concepts in Research and Data Analysis
1(26)
Introduction: A Common Language for Researchers
2(1)
Steps to Follow When Conducting Research
3(3)
Variables, Values, and Observations
6(3)
Scales of Measurement and JMP Modeling Types
9(3)
Basic Approaches to Research
12(4)
Descriptive versus Inferential Statistical Analysis
16(1)
Hypothesis Testing
17(8)
Summary
25(1)
References
25(2)
Getting Started with JMP
27(12)
Starting the JMP Application
28(1)
The JMP Approach to Statistics
29(1)
A Step-by-Step JMP Example
30(8)
Summary
38(1)
References
38(1)
Working with JMP Data
39(32)
Structure of a JMP Table
40(3)
JMP Tables, Rows, and Columns
43(8)
Getting Data into JMP
51(7)
Data Table Management
58(12)
Summary
70(1)
References
70(1)
Exploring Data with the Distribution Platform
71(32)
Why Perform Simple Descriptive Analyses?
72(1)
Example: The Helpfulness Social Survey
73(3)
Computing Summary Statistics
76(7)
Testing for Normality
83(17)
A Step-by-Step Distribution Analysis Example
100(1)
Summary
100(1)
References
101(2)
Measures of Bivariate Association
103(34)
Significance Tests versus Measures of Association
104(1)
Choosing the Correct Statistic
105(5)
Pearson Correlations
110(13)
Spearman Correlations
123(1)
The Chi-Square Test of Independence
124(9)
Fisher's Exact Test for 2 by 2 Tables
133(1)
Summary
134(1)
Assumptions Underlying the Tests
135(1)
References
136(1)
Assessing Scale Reliability with Coefficient Alpha
137(16)
Introduction: The Basics of Scale Reliability
138(3)
Cronbach's Alpha
141(1)
Computing Cronbach's Alpha
142(8)
Summarizing the Results
150(1)
Summary
151(1)
References
151(2)
t Tests: Independent Samples and Paired Samples
153(40)
Introduction: Two Types of t Tests
154(1)
The Independent-Samples t Test
155(19)
The Paired-Samples t Test
174(15)
Summary
189(1)
Assumptions Underlying the t Test
190(2)
References
192(1)
One-Way ANOVA with One Between-Subjects Factor
193(26)
Introduction: One-Way ANOVA Between-Subjects Design
194(4)
Example with Significant Differences between Experimental Conditions
198(14)
Example with Nonsignificant Differences between Experimental Conditions
212(3)
Understanding the Meaning of the F Statistic
215(2)
Summary
217(1)
Assumptions Underlying One-Way ANOVA with One Between-Subjects Factor
217(1)
References
218(1)
Factorial ANOVA with Two Between-Subjects Factors
219(40)
Introduction to Factorial Designs
220(3)
Some Possible Results from a Factorial ANOVA
223(8)
Example with Nonsignificant Interaction
231(18)
Example with a Significant Interaction
249(7)
Summary
256(1)
Assumptions for Factorial ANOVA with Two Between-Subjects Factors
256(1)
References
257(2)
Multivariate Analysis of Variance (MANOVA) with One Between-Subjects Factor
259(22)
Introduction: Multivariate Analysis of Variance (MANOVA)
260(6)
Example with Significant Differences between Experimental Conditions
266(10)
Example with Nonsignificant Differences between Experimental Conditions
276(2)
Summary
278(1)
Assumptions Underlying MANOVA with One Between-Subjects Factor
279(1)
References
280(1)
One-Way ANOVA with One Repeated-Measures Factor
281(34)
Introduction: What Is a Repeated-Measures Design?
282(2)
Example: Significant Differences in Investment Size Across Time
284(13)
Repeated-Measures Design versus Between-Subjects Design
297(3)
Univariate or Multivariate ANOVA for Repeated-Measures Analysis
300(11)
Summary
311(1)
Assumptions of the Multivariate Analysis of Design with One Repeated-Measures Factor
312(1)
References
312(3)
Factorial ANOVA with Repeated-Measures Factors and Between-Subjects Factors
315(46)
Introduction: Mixed-Design ANOVA
316(6)
Possible Results from a Two-Way Mixed-Design ANOVA
322(5)
Problems with the Mixed-Design ANOVA
327(1)
Example with a Nonsignificant Interaction
328(18)
Example with a Significant Interaction
346(8)
An Alternative Approach to a Univariate Repeated-Measures Analysis
354(3)
Summary
357(1)
Assumptions for Factorial ANOVA with Repeated-Measures and Between-Subjects Factors
358(2)
References
360(1)
Multiple Regression
361(56)
Introduction to Multiple Regression
362(6)
Predicting a Response from Multiple Predictors
368(10)
The Results of a Multiple Regression Analysis
378(16)
Example: A Test of the Investment Model
394(3)
Computing Simple Statistics and Correlations
397(4)
Estimating the Full Multiple Regression Equation
401(7)
Uniqueness Indices for the Predictors
408(1)
Summarizing the Results
409(1)
Getting the Big Picture
410(1)
Formal Description of Results for a Paper
411(1)
Summary
412(1)
Assumptions Underlying Multiple Regression
413(2)
References
415(2)
Principal Component Analysis
417(42)
Introduction to Principal Component Analysis
418(9)
The Prosocial Orientation Inventory
427(3)
Using the Multivariate Platform
430(2)
Conducting the Principal Component Analysis
432(20)
A Graphical Approach to Principal Components
452(4)
Summary
456(1)
Assumptions Underlying Principal Component Analysis
457(1)
References
457(2)
Appendix Choosing the Correct Statistic
459(8)
Introduction: Thinking about the Number and Scale of Your Variables
460(3)
Guidelines for Choosing the Correct Statistic
463(3)
Summary
466(1)
Index 467

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