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Basic Statistical Analysis,9780205296415
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Basic Statistical Analysis

by
ISBN13:

9780205296415

ISBN10:
0205296416
Format:
Hardcover
Pub. Date:
9/1/1999
Publisher(s):
Prentice Hall
List Price: $92.00
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Summary

This user-friendly, readable revision is presented as simply as possible to ensure that students will gain a solid understanding of statistical procedures. The goal of this book is to demystify statistics. The student is presented with rules of evidence and the logic behind those rules. The book is divided into three major units: Descriptive Statistics, Inferential Statistics, and Advanced Topics in Inferential Statistics.

Table of Contents

Preface vii
UNIT I DESCRIPTIVE STATISTICS 1(126)
1 Introduction to Statistics
3(16)
Stumbling Blocks to Statistics
4(8)
A Brief Look at the History of Statistics
12(2)
Benefits of a Course in Statistics
14(1)
General Field of Statistics
14(2)
Summary
16(1)
Key Terms and Names
17(1)
Problems
17(2)
2 Graphs and Measures of Central Tendency
19(24)
Graphs
19(7)
Measures of Central Tendency
26(9)
Appropriate Use of the Mean, the Median, and the Mode
35(4)
Summary
39(1)
Key Terms
40(1)
Problems
40(2)
Computer Problems
42(1)
3 Variability
43(18)
Measures of Variability
44(9)
Graphs and Variability
53(3)
Summary
56(1)
Key Terms
57(1)
Problems
57(3)
Computer Problems
60(1)
4 The Normal Curve and z Scores
61(24)
The Normal Curve
61(4)
z Scores
65(8)
Translating Raw Scores into z Scores
73(4)
z Score Translations in Practice
77(5)
Summary
82(1)
Key Terms and Names
82(1)
Problems
82(3)
5 z Scores Revisited: T Scores and Other Normal Curve Transformations
85(22)
Other Applications of the z Score
85(1)
The Percentile Table
86(9)
T Scores
95(3)
Normal Curve Equivalents
98(1)
Stanines
98(1)
Grade-Equivalent Scores: A Note of Caution
99(3)
The Importance of the z Score
102(1)
Summary
103(1)
Key Terms
104(1)
Problems
104(3)
6 Probability
107(20)
The Definition of Probability
107(7)
Probability and Percentage Areas of the Normal Curve
114(5)
Combining Probabilities for Independent Events
119(3)
A Reminder about Logic
122(1)
Summary
122(1)
Key Terms
123(1)
Problems
123(4)
UNIT II INFERENTIAL STATISTICS 127(236)
7 Statistics and Parameters
129(27)
Generalizing from the Few to the Many
129(1)
Key Concepts of Inferential Statistics
130(2)
Techniques of Sampling
132(8)
Sampling Distributions
140(8)
Back to z
148(3)
Some Words of Encouragement
151(1)
Summary
151(1)
Key Terms
152(1)
Problems
152(4)
8 Parameter Estimates and Hypothesis Testing
156(23)
The Standard Deviation Revisited
156(2)
Estimating the Standard Error of the Mean
158(1)
Estimating the Population Mean: Interval Estimates and Hypothesis Testing
159(1)
The t Ratio
160(5)
The Type 1 Error
165(1)
Alpha Levels
166(3)
Effect Size
169(1)
Interval Estimates: No Hypothesis Test Needed
170(4)
Summary
174(1)
Key Terms
174(1)
Problems
175(2)
Computer Problems
177(2)
9 The Fundamentals of Research Methodology
179(40)
Research Strategies
180(1)
Independent and Dependent Variables
181(2)
The Causes and-Effect Trap
183(1)
Theory of Measurement
184(5)
Research: Experimental versus Post-Facto
189(1)
The Experimental Method: The Case of Cause and Effect
189(3)
Creating Equivalent Groups: The True Experiment
192(2)
Designing the True Experiment
194(3)
The Hawthorne Effect
197(1)
Sequencing Effects
198(1)
Counterbalancing
198(1)
Repeated Measures Designs with Separate Control Groups
199(2)
Requirements for the True Experiment
201(1)
Post-Facto Research
202(3)
Combination Research
205(1)
Research Errors
206(2)
Experimental Error: Failure To Use an Adequate Control Group
208(1)
Post-Facto Errors
209(2)
Meta-Analysis
211(2)
Methodology as a Basis for More Sophisticated Techniques
213(1)
Summary
213(2)
Key Terms
215(1)
Problems
216(3)
10 The Hypothesis of Difference
219(36)
Sampling Distribution of Differences
220(3)
Estimated Standard Error of Difference
223(2)
Two-Sample t Test for Independent Samples
225(3)
Significance
228(4)
Two-Tail t Table
232(2)
Alpha and Confidence Levels
234(2)
The Minimum Difference
236(1)
Outliers
236(1)
One-Tail t Test
237(4)
Importance of Having at Least Two Samples
241(1)
Power
242(1)
Effect Size
243(4)
Summary
247(1)
Key Terms
248(1)
Problems
249(3)
Computer Problems
252(3)
11 The Hypothesis of Association: Correlation
255(40)
Cause and Effect
255(3)
The Pearson r
258(1)
Interclass versus Intraclass
258(17)
Correlation Matrix
275(2)
The Spearman r(s)
277(7)
An Important Difference between the Correlation Coefficient and the t Test
284(1)
Summary
284(1)
Key Terms and Names
285(1)
Problems
285(6)
Computer Problems
291(4)
12 Analysis of Variance
295(37)
Advantages of ANOVA
295(2)
Analyzing the Variance
297(14)
Applications of ANOVA
311(1)
The Factorial ANOVA
312(7)
Eta squared and d
319(1)
Graphing the Interaction
320(4)
Summary
324(1)
Key Terms and Names
325(1)
Problems
325(4)
Computer Problems
329(3)
13 Nominal Data and the Chi Square
332(31)
Chi Square and Independent Samples
331(11)
Locating the Difference
342(2)
Chi Square and Percentages
344(2)
Chi Square and z Scores
346(1)
Chi Square and Dependent Samples
346(6)
Requirements for Using the Chi Square
352(1)
Summary
352(1)
Key Terms and Names
353(1)
Problems
353(6)
Computer Problems
359(4)
UNIT III ADVANCED TOPICS IN INFERENTIAL STATISTICS 363(162)
14 Regression Analysis
365(37)
Regression of Y on X
365(12)
Standard Error of Estimate
377(3)
Confidence Interval Equation
380(1)
Multiple R (Linear Regression with More Than Two Variables)
381(7)
Path Analysis, the Multiple R, and Causation
388(1)
Partial Correlation
389(4)
Summary
393(1)
Key Terms and Names
394(1)
Problems
394(5)
Computer Problems
399(3)
15 Repeated-Measures and Matched-Subjects Designs with Interval Data
402(30)
Problem of Correlated or Dependent Samples
402(2)
Repeated Measures
404(1)
Paired t Ratio
404(12)
Within-Subjects F Ratio
416(3)
Within-Subjects Effect Size
419(2)
Testing Correlated and Experimental Data
421(1)
Summary
422(1)
Key Terms
423(1)
Problems
423(5)
Computer Problems
428(4)
16 Nonparametrics Revisited: The Ordinal Case
432(16)
Mann-Whitney U Test for Two Ordinal Distributions with Independent Selection
433(3)
Kruskal-Wallis H Test for Three or More Ordinal Distributions with Independent Selection
436(2)
Wilcoxon T Test for Two Ordinal Distributions with Correlated Selection
438(2)
Friedman ANOVA by Ranks for Three or More Ordinal Distributions with Correlated Selection
440(2)
Advantages and Disadvantages of Nonparametric Tests
442
Summary
422
Key Terms
443(1)
Problems
443(5)
17 Tests and Measurements
448(38)
Norm and Criterion Referencing: Relative versus Absolute Performance Measures
449(1)
The Problem of Bias
450(1)
Test Reliability, Validity, and Measurement Theory
451(12)
Test Validity
463(6)
Item Analysis
469(8)
Summary
477(2)
Key Terms and Names
479(1)
Problems
479(5)
Computer Problems
484(2)
18 Computers and Statistical Analysis
486(12)
Computer Literacy
487(2)
The Statistical Programs
489(4)
Logic Checkpoints
493(3)
Answers
496(1)
Recommended Reading
497(1)
19 Research Simulations: Choosing the Correct Statistical Test
498(27)
Methodology: Research's Bottom Line
498(1)
Checklist Questions
499(2)
Critical Decision Points
501(1)
Research Simulations: From A to Z
501(22)
The Research Enterprise
523(1)
A Final Thought: The Burden of Proof
524(1)
Special Unit: The Binomial Case 525(14)
Appendix A 539(18)
Appendix B 557(32)
Glossary 589(13)
References 602(5)
Answers to Odd-Numbered Items (and Within-Chapter Exercises) 607(10)
Index 617


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